Journal of Medical and Health Studies (ISSN: 2710-1452) is a peer-reviewed International Journal published by Al-Kindi Center for Research and Development. The journal covers scholarly articles in the fields of Medicine and Public Health. All articles are freely available without charge to the users or their institutions; thus, ensuring high visibility and increasing citations for all research articles published. The journal aims to facilitate scholarly work on recent theoretical and practical aspects of health and medical sciences. Academics, policymakers, and researchers are welcome to submit their manuscripts at any time.
Al-Kindi Center for Research and Development
Deep Learning–Based Skin Cancer Diagnosis in the United States: Advances, Challenges, and Clinical Translation
Skin cancer represents one of the most common and potentially fatal malignancies in the United States. Where timely and accurate diagnosis is critical for reducing mortality and healthcare burden. Current diagnostic practices, including visual examination and dermoscopy. This rely heavily on clinician expertise and are subject to inter-observer variability, particularly in early-stage disease. In recent years, deep learning has emerged as a promising tool for automating skin cancer detection from dermoscopic images. With offering improved diagnostic accuracy and scalability. This article provides a comprehensive analysis of deep learning-based approaches for skin cancer classification, with a focus on convolutional neural network architectures, commonly used datasets, and performance evaluation metrics relevant to U.S. clinical settings. Key challenges, including dataset imbalance, limited representation of diverse skin tones, overfitting on small cohorts, and high computational demands, are critically examined. Additionally, the study discusses emerging trends toward lightweight and deployable models suited for real-time clinical workflows and mobile health applications within the United States healthcare system. The findings aim to support the development of robust, generalizable, and clinically translatable deep learning solutions for skin cancer diagnosis.
Skin cancer detection, Deep learning, Convolutional neural networks, Dermoscopic images, Medical image classification, Dataset bias, Lightweight models, Computer-aided diagnosis
Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
Streamlining Clinical Endorsement: Electronic Sbar-Integrated Clinical Handover Management Framework
This study aimed to develop an electronic Situation–Background–Assessment– Recommendation (e-SBAR) system framework for nurses at South General Hospital, City of Naga. It employed a descriptive–comparative research design to assess nurses’ perceptions and challenges in implementing the manual SBAR tool and to identify key system features necessary for digital transition. The research was conducted at South General Hospital, a tertiary Level II facility under the CebuDoc Group. Using total sampling, the study involved fifty-five (55) nurse respondents across departments, namely Outpatient, Pediatrics, Emergency Room, Operating Room, Medical–Surgical Ward, Intensive Care Unit, and OB-Gyne Ward, along with selected information technology experts. Data were gathered through two researcher-developed instruments the SBAR Perceptions and Challenges Questionnaire and the SBAR System Features Checklist. Findings revealed that while SBAR was moderately practiced across departments, several operational challenges persisted, particularly time pressure, workload, and contextual limitations. The study concluded that digital standardization through an e-SBAR system could improve communication accuracy, patient safety, and workflow efficiency. It was strongly recommended that South General Hospital adopt and implement the proposed electronic SBAR system framework as a hospital-wide tool for clinical handover.
SBAR Communication Tool, Nurse Handover, Patient Safety, Communication Barriers
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
Clinicopathological Characteristics, Diagnosis, and Management of Ovarian Cancer: A Systematic Review
Ovarian cancer remains one of the leading causes of gynecological cancer-related mortality worldwide due to its insidious onset, late-stage diagnosis, and complex biological behavior. Despite advances in imaging, molecular diagnostics, and therapeutic strategies, overall survival rates remain suboptimal. This systematic review aims to synthesize current evidence on the clinicopathological characteristics, diagnostic approaches, and management strategies of ovarian cancer. A comprehensive literature search was conducted across PubMed, Scopus, Web of Science, and Google Scholar for studies published between 2015 and 2024. A total of 20 sources were included, consisting of 17 peer-reviewed journal articles and 3 authoritative textbooks. Data were extracted on epidemiology, histopathological subtypes, molecular features, clinical presentation, diagnostic modalities, and treatment outcomes. The findings highlight that epithelial ovarian cancer, particularly high-grade serous carcinoma, represents the most prevalent and aggressive subtype. Late-stage presentation (FIGO stage III–IV) remains common, contributing significantly to poor prognosis. Multimodal management involving cytoreductive surgery and platinum-based chemotherapy continues to be the cornerstone of treatment, while targeted therapies and immunotherapy are emerging as promising adjuncts. This review underscores the importance of early detection strategies, standardized pathological classification, and personalized treatment approaches to improve survival outcomes in ovarian cancer patients.
Copyright (c) 2026 Journal of Medical and Health Studies
Physiological and Molecular Characterization of “Hormonal Receptors and “HER-2/Neu” in Breast Cancer
The hormonal, reproductive and demographic factors all affect the clinical course of breast cancer, which is an important health problem that remains unresolved. CAans and MVG: / Comparison of primary versus metastatic breast cancer characteristics This study aimed to evaluate the characteristics of PBC + MBC. A descriptive analytical study was performed on the patients with primary and metastatic breast cancer to identify demographic, reproductive, clinical, histopathological, and hormonal factors. The average age of the patients was 42 years. The incidence of primary breast cancer occurred at 51–55 years, whereas for metastatic disease, it was at 36–40 years. In 22.5% of primary patients, a history of AML was present and 35% had metastatic disease. Precocious menarche at 12–14 years has been described in 57% patients. The majority of patients were multiparous (75%) and 72% experienced their primiparity at or ≤25 years. Breast feeding accounted for 55.2% of primary and 47.1% of metastatic patients. The majority of patients were post-menopausal women. Incidence of axillary lymph nodes was 85% in primary and 80% in mets. Stage II was the most common (60%) followed by stage IV (26%). IDC accounted for the most common type of tumor (81%). Primary–metastatic sites, hormone receptors ER 67.8% and 54.66%, PR 66.6% and 63%; HER2Neu was significantly more positive in metastasis cases (62.7%) than in primaries (53.5%). Breast cancer in the research population is early onset, and a high proportion of the cohort developed advanced disease. Reproductive factors and hormones, molecular tumor features have the tendency to shape the course of disease, emphasizing early diagnosis and personalized screening programs.
Breast cancer; Reproductive factors; Estrogen receptor (ER)”; Progesterone receptor (PR)”, “Immunohistochemistry”
Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
Endometriosis and the Silent Heart Risk: A Systematic Review of Cardiovascular Disease in Affected Women
Endometriosis affects approximately 10% of reproductive-aged women worldwide and is increasingly recognized as a chronic systemic inflammatory condition that may contribute to cardiovascular disease (CVD). We conducted a PRISMA 2020–guided systematic review to evaluate the association between endometriosis and cardiovascular outcomes. We searched PubMed (Medline), Embase, Scopus, and Web of Science for observational studies and meta-analyses published between January 2000 and May 2025, with emphasis on evidence from 2019–2025. Eligible studies compared cardiovascular outcomes in women with clinically or surgically diagnosed endometriosis versus women without endometriosis. Outcomes included myocardial infarction, ischemic heart disease, stroke, hypertension, arrhythmias, heart failure, atherosclerotic markers, and venous thromboembolism. Two reviewers independently screened records, extracted data, and assessed study quality following PRISMA guidance. Large cohort studies and recent meta-analyses consistently demonstrate higher cardiovascular risk among women with endometriosis. Adjusted hazard ratios reported in primary studies ranged from 1.12 for new-onset hypertension to 1.52 for coronary artery disease. Meta-analyses including over 1.4 million women reported pooled hazard ratios of ~1.35 for ischemic heart disease and ~1.19 for cerebrovascular disease. Subclinical studies show impaired endothelial function and increased markers of early atherosclerosis in women with endometriosis. Endometriosis is associated with a modest but consistent increase in risk of several cardiovascular outcomes across diverse populations and study designs. These findings support systematic cardiovascular risk assessment and appropriate preventive strategies in women with endometriosis.
Impact of an Educational Intervention on Laboratory Technicians’ Knowledge of HIV Screening in the Northern Borders Region of Saudi Arabia
Ensuring the accuracy of HIV screening in blood banks is essential for maintaining transfusion safety and preventing transfusion-transmitted infections. This study evaluated the effectiveness of an educational intervention designed to improve HIV-related knowledge among laboratory technicians in the Central Blood Bank of the Northern Borders Region of Saudi Arabia. A quantitative descriptive design was employed, using a structured questionnaire administered before and after a targeted training program. Thirty laboratory technicians participated, completing assessments covering HIV transmission, diagnostic methods, quality assurance procedures, and biosafety practices. Paired t-test analysis demonstrated a statistically significant improvement in knowledge following the intervention, with mean scores increasing from 11.07 to 14.00 (p < 0.001). Effect size calculations indicated a large practical impact (Cohen’s d = 0.842), and internal consistency of the instrument improved from α = 0.762 pre-intervention to α = 0.794 post-intervention. Descriptive and frequency analyses revealed notable reductions in misconceptions related to the diagnostic window period, rapid test identification, test sensitivity, and WHO/UNAIDS testing strategies. The findings underscore the critical role of structured, continuous training in enhancing laboratory competency, standardizing testing practices, and reinforcing quality assurance within HIV screening services. Implementing routine, evidence-based educational programs can strengthen national blood safety systems and support alignment with international standards for HIV testing and transfusion safety.
Copyright (c) 2025 Journal of Medical and Health Studies
The Role of Parent–Child Attachment and Sleep Hygiene in the Development of ADHD in Children
Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifactorial neurodevelopmental condition shaped by biological, environmental, and psychosocial influences. Beyond genetic vulnerability, emerging evidence highlights the developmental significance of contextual factors such as parent–child attachment, sleep hygiene, and emotional competence. This literature review synthesizes empirical findings examining how these three domains contribute to the development of ADHD in children. Understanding these mechanisms may help inform more comprehensive, family-centered approaches to ADHD prevention and management. Secure parent–child attachment was consistently associated with better emotional regulation, internalization of behavioral control, and reduced ADHD symptomatology, whereas maternal anxiety and low emotional availability were linked to greater symptom severity. Sleep hygiene also demonstrated a strong relationship with ADHD manifestations, with poor sleep routines, sleep disturbances, and inadequate sleep quality correlating with higher levels of inattention, hyperactivity, and emotional dysregulation. Interventions targeting sleep hygiene have been shown to improve both sleep and behavioral outcomes in ADHD populations. Furthermore, studies examining attachment and sleep jointly show that secure attachment promotes healthier sleep quality, and sleep quality partially mediates the relationship between attachment and well-being. In conclusion, the literature suggests that parent–child relational processes and sleep-related behaviors interact to shape self-regulatory development, which may influence ADHD symptoms.
A Rare Chest Presentation of Inflammatory Bowel Disease: Spontaneous Pneumomediastinum in Crohn’s Disease
We report the case of a 46-year-old man with long-standing Crohn’s disease who presented with acute central chest discomfort and dyspnea, following an episode of forceful vomiting. His gastrointestinal symptoms had been mild and self-managed, with no prior history of fistulizing disease. Physical examination revealed mild central chest tenderness and shallow breathing without overt respiratory distress. Initial chest radiography demonstrated mediastinal air consistent with pneumomediastinum. Subsequent contrast-enhanced CT scans of the chest, abdomen, and pelvis revealed free air tracking from a thickened terminal ileal segment through the retroperitoneum into the posterior mediastinum, suggesting a contained microperforation with a developing fistula. Laboratory workup showed mild elevation of inflammatory markers, with otherwise stable hematologic and metabolic parameters. The patient was admitted for conservative management, including supplemental oxygen, bowel rest, intravenous fluids, analgesia, and targeted antibiotics. Serial imaging and clinical monitoring demonstrated gradual resolution of mediastinal air without progression to pneumothorax or abscess. Gastroenterology follow-up focused on optimization of Crohn’s therapy to prevent recurrence. This case underscores the rare but clinically significant occurrence of pneumomediastinum secondary to fistulizing Crohn’s disease. Early recognition through imaging, careful monitoring, and multidisciplinary management allowed for a favorable outcome. Awareness of subtle respiratory manifestations in Crohn’s disease is essential to prevent misdiagnosis and guide appropriate care.
Crohn’s disease, Ulcerative colitis, Inflammatory bowel disease, Spontaneous pneumomediastinum, Dyspnea, Shortness of breath.
Clinical Severity and Quality of Life Impairment in Vitiligo: A Literature Review on the Relationship Between VASI and DLQI
Vitiligo poses a long term challenge that affects not just physical appearance but also emotional health and daily life. People living with the condition often face difficulties related to the visibility of skin changes, the unpredictable nature of the disease, and how others in society respond to it, all of which significantly affect their overall quality of life. Recent research highlights the importance of understanding the impact of vitiligo through both medical and personal accounts. Two commonly used tools, the Vitiligo Area Scoring Index (VASI) and the Dermatology Life Quality Index (DLQI), provide different but complementary views on how the loss of skin color relates to emotional and social effects. This review brings together findings from recent studies to explore how these measures connect and what they reveal about the lived experience of vitiligo. VASI measures the size and spread of depigmented patches, while DLQI looks at how these changes affect emotions, social relationships, work, and self esteem. Research across various settings consistently shows that more severe disease is linked to greater impairment in quality of life, although the strength of this link can vary based on factors like age, how long someone has had the condition, the level of stigma they face, and cultural background. The available evidence suggests that using both VASI and DLQI together gives a more complete understanding of the burden of vitiligo than using either one alone, highlighting the importance of considering both visible and hidden aspects of the condition. New studies also suggest that psychological support, early counseling, and tailored treatment plans may help reduce the difference between the severity of the disease as seen by doctors and how much distress it causes the individual. By combining insights from dermatology, psychology, and patient reported outcomes, this review emphasizes the value of using a multidimensional approach in vitiligo care. Future research should use long term and culturally diverse methods to better understand how disease severity and perceptions of quality of life change over time, and to improve interventions that support the overall well being of people with vitiligo.
Vitiligo, VASI, DLQI, quality of life, disease burden, psychosocial dermatology
Psychobiological Markers, Coping Mechanisms, and Family Well-being in Attention Deficit Hyperactivity Disorder (ADHD)
Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental condition arising from a complex interplay of genetic and environmental factors, reflected through diverse psychobiological markers involving neurophysiology, neurochemistry, neuroimaging, and molecular profiles. Various biomarkers, including electrophysiological changes, alterations in functional connectivity, neurotransmitter variations, and miRNA expression, have been associated with ADHD, although none have yet demonstrated consistent diagnostic sensitivity. Individuals with ADHD frequently display maladaptive coping strategies such as avoidance and escape behaviors, contributing to emotional dysregulation and reduced quality of life. These difficulties extend to the family environment, where caregivers often experience heightened stress, strained interactions, disrupted daily routines, and increased psychological burden. Studies indicate that family functioning, parenting quality, and stress levels are closely linked to ADHD symptom severity, affecting both the individual and their caregivers. However, the use of adaptive coping strategies, such as problem solving, cognitive restructuring, and social support, can strengthen resilience, reduce psychological strain, and improve overall family well-being. Integrating knowledge of psychobiological markers with patterns of coping and family dynamics provides a more comprehensive understanding of ADHD and highlights the importance of supporting adaptive coping mechanisms to improve outcomes for individuals with ADHD and their families.
The Role of Neutrophil Gelatinase-Associated Lipocalin (NGAL) in the Early Detection of Nephrotoxicity caused by Chemotherapy for Breast Cancer
Chemotherapy remains a cornerstone of breast cancer management; however, its potential to induce renal injury continues to pose substantial clinical challenges. Early identification of kidney impairment is essential to prevent irreversible damage and to maintain the safety and continuity of cancer treatment. Conventional indicators such as serum creatinine and estimated glomerular filtration rate (eGFR) lack sufficient sensitivity because they typically increase only after considerable nephron loss has occurred. Neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a promising early biomarker for renal injury Synthesized by renal tubular epithelial cells and neutrophils in response to tissue damage, NGAL levels can rise within hours following exposure to nephrotoxic agents. This review examines the role of NGAL in detecting chemotherapy-related nephrotoxicity among breast cancer patients, drawing on evidence from both clinical and experimental studies. Post-chemotherapy elevations in NGAL frequently precede detectable changes in serum creatinine, highlighting its capacity to identify subclinical tubular injury. Nonetheless, additional prospective studies employing standardized measurement protocols are needed to further validate the diagnostic accuracy and clinical utility of NGAL.
NGAL, nephrotoxicity, chemotherapy, breast cancer, biomarker.
The Unexpected Diagnosis: Refractory Pneumonia as The First Manifestation of HIV in a Low-risk Individual
A 39-year-old previously healthy Saudi man presented with a six-week history of persistent dry cough, intermittent low-grade fever, chest heaviness, and progressive exertional dyspnea unresponsive to three outpatient antibiotic courses. Imaging revealed a new extensive pneumonic patch in the left lower and middle lobes contrasting with prior normal chest radiographs, while high-resolution CT demonstrated patchy ground-glass opacities without consolidation or cavitation. Laboratory studies showed mild anemia, leukopenia, slightly elevated inflammatory markers, and a reduced CD4 count, raising concern for underlying immunodeficiency. Routine bacterial, mycobacterial, and fungal investigations were negative, but sputum PCR confirmed Pneumocystis jirovecii, and subsequent HIV testing was positive. The patient was admitted to a monitored unit, received supplemental oxygen, and initially broad-spectrum intravenous antibiotics, followed by targeted high-dose trimethoprim-sulfamethoxazole therapy. Supportive measures included hydration, respiratory physiotherapy, nutritional optimization, and close monitoring of oxygenation, laboratory parameters, and clinical status. Antiretroviral therapy was deferred until stabilization to mitigate the risk of immune reconstitution inflammatory syndrome, with a coordinated long-term plan for secondary prophylaxis, CD4 and viral load monitoring, and follow-up imaging. This case highlights the critical need to consider HIV and opportunistic infections in adults with nonresolving pneumonia regardless of prior health status, demonstrates the importance of integrating radiographic, laboratory, and immunologic data for accurate diagnosis, and underscores the value of prompt targeted therapy combined with multidisciplinary management to optimize recovery, prevent complications, and guide long-term care.
HIV, AIDS, Pneumonia, Refractory Pneumonia, CD4 Count, Viral Load, Pneumocystis jirovecii.
The Unlikely Duo: Gross Hematuria and Clubbing Revealing Hidden Malignancy
A previously healthy 47-year-old Saudi male presented with a two-month history of painless gross hematuria and notable digital clubbing. The hematuria was intermittent, dark red, and unassociated with dysuria, flank pain, or systemic symptoms. Physical examination confirmed clubbing of the fingers, while vital signs and general assessment were unremarkable. Laboratory evaluation revealed mild polycythemia and borderline hypercalcemia, with otherwise normal renal and liver function. Urinalysis excluded infection or glomerular disease, and urinary cytology was negative for urothelial malignancy. Given the combination of persistent hematuria and paraneoplastic signs, imaging studies were prioritized. Renal ultrasonography identified a heterogeneous right upper pole mass, subsequently characterized by contrast-enhanced CT as a 6-cm right renal mass with heterogeneous enhancement and areas of necrosis, consistent with renal cell carcinoma (RCC), without evidence of metastasis. Multidisciplinary discussion favored radical nephrectomy, which was performed successfully with en bloc excision of the kidney, perinephric fat, and regional lymph nodes. Histopathology confirmed clear cell RCC, Fuhrman grade II, with negative margins and no lymphovascular invasion (pT1bN0M0). Postoperatively, hematuria resolved, and early regression of clubbing was observed. This case highlights the diagnostic significance of gross hematuria combined with paraneoplastic manifestations such as clubbing, emphasizing the importance of early imaging and prompt surgical intervention for localized RCC to optimize outcomes.
Malignancy, Renal Cell Carcinoma, Clubbing, Gross Hematuria, Painless Hematuria, Paraneoplastic Syndrome.
The Mechanism of Antiviral Action with Acupuncture Based on COVID-19: Antiviral Action and Acupuncture
The virus that created COVİD-19 is a pathogen that enters the cell, multiplies, spreads and creates pathology by disrupting the functioning of the body throughout the extracellular environment. The most important step in fighting this pathogen is to prevent the virus from entering the cell. The second step is to inhibit the polymerase enzyme to prevent it from multiplying in the cell, and in the third step, to form antibodies against the protein formed. In the current medical system, it is out of question to receive news from within the cell. The vascular, lymphatic and nervous systems have no connection with the intracellular environment. The acupuncture channel (meridian) system, also known as the primordial system, has intracellular extensions. And these extensions have a connection with the outside. In accordance with the concept of the new cell, the meridian system has an external relationship. Acupuncture treatment affects through these relations. However, a model describing the antiviral mechanism of action with acupuncture is not yet available. In this study, we tried to create such a model by making use of western medicine.
Chronic Thromboembolic Pulmonary Hypertension Manifesting as Exertional Limitation: A Clinical Diagnostic Perspective
Chronic thromboembolic pulmonary hypertension (CTEPH) is a rare but potentially progressive cause of pulmonary hypertension, often presenting with subtle exertional symptoms that delay diagnosis. We report the case of a 34-year-old man with no prior chronic medical conditions who presented with a three-month history of progressive exertional dyspnea and fatigue, accompanied by intermittent lower extremity edema and Raynaud-like color changes in the toes. Physical examination revealed mild ankle edema and subtle digital clubbing, with otherwise unremarkable cardiopulmonary and musculoskeletal findings. Laboratory evaluation showed elevated NT-proBNP, modestly raised D-dimer, and preserved renal and hepatic function. Transthoracic echocardiography revealed right ventricular dilation with preserved systolic function and an estimated pulmonary artery systolic pressure of 62 mmHg. Pulmonary function testing was largely normal, but computed tomography pulmonary angiography demonstrated organized thrombotic material in segmental and subsegmental pulmonary arteries bilaterally. Right heart catheterization confirmed pre-capillary pulmonary hypertension. Further evaluation revealed combined congenital deficiencies of protein S and protein C, explaining the thrombotic predisposition in the absence of prior venous thromboembolic events. The patient was managed with anticoagulation, cautious diuresis, supportive therapy, and initiation of pulmonary vasodilator therapy, with referral to a specialized center for consideration of surgical intervention. This case emphasizes the importance of thorough clinical evaluation, early imaging, and hemodynamic assessment in young adults presenting with unexplained exertional limitation. Recognition of underlying thrombophilic disorders is crucial to guide management, prevent recurrent thrombosis, and preserve right ventricular function, underscoring the value of a multidisciplinary approach in optimizing long-term outcomes in CTEPH.
Shortness of breath, Dyspnea, Chronic thrombo-embolic pulmonary embolism, CTEPH, Protein S\C deficiency, Thrombophilia.
Robotic Surgical Systems in Orthopaedics: Clinical Efficacy, Economic Evaluation, and Implementation Challenges
Orthopaedic surgery is rapidly undergoing a technological transformation, driven by the integration of digital navigation, computer-assisted planning, and robotic systems. Robotic surgical systems are primarily used in knee and hip arthroplasty, as well as spinal surgery, with the goals of improving implant placement accuracy, reducing complication rates, and enhancing patient safety. These technologies have an impact on operation duration, error rates, and learning curves depending on the surgeon’s level of experience. However, high capital investment, maintenance costs, and consumables mean that cost-effectiveness is closely linked to case volume. Thus, the economic sustainability of robotic systems depends not only on technological efficiency but also on high procedure volume, appropriate reimbursement policies, and interdisciplinary operational integration. From an ethical and legal perspective, the spread of robotic surgery has brought new issues to the fore, such as responsibility sharing, transparency of AI-assisted decision systems, data security, and informed consent processes. In terms of clinical management, safe and effective implementation of robotic surgery requires standardized training programs for surgeons and teams, ongoing technical support, and clear, understandable policies and regulations. This review examines orthopaedic robotic surgery in terms of clinical efficacy, economic evaluation, and management, aiming to propose a holistic approach for the safe, ethical, and financially sustainable integration of technology into healthcare systems.
Robotic surgery, orthopaedics, cost-effectiveness, health economics, artificial intelligence, ethical management, clinical effectiveness, ROI
Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/
Applying Artificial Intelligence to Improve Early Detection and Containment of Infectious Disease Outbreaks, Supporting National Public Health Preparedness
The swift transmission of infectious diseases constitutes a serious global public health problem and therefore there is a need for sophisticated tools to improve early detection and containment measures. Artificial Intelligence (AI) has become a powerful tool in the transformation of public health preparedness as a means of providing real-time intelligence, predictive modeling and data-driven interventions. This article explores the application of AI in the improvement of early detection of infectious diseases outbreaks and improved containment efforts. We go over some use cases that are important in recent studies, including AI-driven surveillance systems, predictive modeling in disease spreading, and big data analytics that works to optimize response strategies. Notably, AI has been instrumental in the face of the current pandemic, known as the Coronavirus or Covid-19, with its role in diagnostics, tracking and developing preventative measures. However, challenges, such as data privacy, cross-sector data integration and algorithmic biases, have to be addressed in order to leverage the full potential of AI. The article also speaks of incorporating AI with other technologies, like telehealth and digital health systems, in creating resilient public health infrastructures. Overall, AI is set to make a significant impact on the preparedness of a country by improving its early warning systems, decision-making, and response coordination efforts which will ultimately reduce the impact of future outbreaks.
Artificial Intelligence, Infectious Disease Outbreaks, Early Detection, Public Health Preparedness, Machine Learning, Predictive Analytics, Disease Surveillance, Health System Optimization, Deep Learning, Generative AI
Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/
Predictive Business Analytics For Reducing Healthcare Costs And Enhancing Patient Outcomes Across U.S. Public Health Systems
The increasing healthcare expenses, especially in U.S. government-funded health systems, are a significant burden to policymakers and medical practitioners. Although the issue of predictive analytics as an intervention in enhancing patient outcomes and cost reduction has gained traction as a concept, there is a knowledge gap in the area of how such technologies can be systematized in large-scale public health environments. The aim of the research was to assess the role of predictive business analytics in terms of healthcare costs and patient outcomes in the U.S. public health systems. The research employed a mixed-methods design, which involved both quantitative analyses of the data on costs and patient outcomes from 50 public health facilities, as well as qualitative analyses of the effectiveness of predictive models. The data were gathered in the electronic health records (EHRs) and examined with the help of regression models, t-tests, and correlation. The results showed that the healthcare costs reduced significantly (mean reduction of 8.5% p < 0.05) and that patient outcomes also improved, with a 12% decline in hospital readmission rates and a 15-point increase in patient satisfaction scores (p < 0.01). These findings highlight the possible opportunities of predictive analytics in streamlining health care delivery and minimizing expenses. The study multiplies the existing literature in the field of application of data-driven decision-making to the field of healthcare, providing empirical evidence of its effectiveness in the public health systems. This study opens the possibilities of wider implementation of predictive analytics tools to improve cost-efficiency and patient care in the field of public health.
healthcare costs, predictive analytics, patient outcomes, public health systems, U.S. healthcare
Copyright (c) 2023 https://creativecommons.org/licenses/by-nc/4.0
AI-Driven Prediction of Mental Disorders: Enhancing Early Diagnosis and Intervention in the USA
Early detection of mental disorders remains one of the most pressing challenges in U.S. public health, as socioeconomic and behavioral indicators often precede clinical diagnosis but are rarely integrated into predictive frameworks. This study develops an AI-driven diagnostic pipeline that fuses demographic, behavioral, and social determinants of health to predict risk for major mental disorders, including anxiety, depression, and post-traumatic stress disorder (PTSD). Using a population-scale dataset of over 10,000 anonymized health records combining age, sex, BMI, income, education, and lifestyle behaviors, we benchmark five machine learning models, Logistic Regression, Random Forest, XGBoost, Support Vector Machine (SVM), and a Multi-Layer Perceptron (MLP), across both unbalanced and SMOTE-balanced conditions. The evaluation integrates multiple dimensions: discrimination (ROC-AUC, PR-AUC), calibration (Brier score, reliability curves), and fairness across demographic subgroups (sex, rural–urban classification). SHAP-based explainability is employed to interpret model behavior and to identify dominant risk predictors and interaction effects, while robustness checks probe performance under covariate shifts and synthetic missingness. Results show that ensemble and deep models outperform classical baselines, with XGBoost achieving an average ROC-AUC of 0.90 and strong calibration stability. Income level, alcohol consumption, and BMI category emerge as top predictors, reflecting known epidemiological associations. Subgroup analysis demonstrates consistent performance across demographic segments, underscoring model fairness and generalizability. Collectively, the findings illustrate how interpretable AI can enhance early detection and risk stratification for mental health conditions, providing a data-driven foundation for preventive interventions, policy guidance, and equitable digital mental health systems in the United States.
Applications of single-cell sequencing in schizophrenia research
Schizophrenia (SCZ) is a highly heritable, severe neuropsychiatric disorder characterized by complex genetic architecture and heterogeneous clinical manifestations. Despite decades of research, the precise molecular and cellular mechanisms underlying its pathogenesis remain incompletely elucidated, which significantly hinders the development of effective preventive strategies and complicates treatment approaches. This comprehensive review systematically examines the emerging application of cutting-edge single-cell sequencing technologies in SCZ research. Single-cell sequencing serves as an unprecedented high-resolution molecular microscope, providing researchers with the remarkable ability to distinguish and characterize the minute individual cellular and molecular components that constitute the extraordinarily complex SCZ "puzzle". The systematic integration of these diverse molecular fragments into a unified, coherent pathophysiological framework holds tremendous promise for yielding transformative research advancements that could fundamentally alter our approach to SCZ diagnosis, treatment, and prevention.
Single-cell sequencing; Schizophrenia (SCZ)
Application of Single-Cell RNA Sequencing Technology: Advancing Targeted Fatty Acids for Antitumor Therapy
The occurrence and progression of tumors are closely linked to the abnormal metabolic mechanism of fatty acids. In tumor cells, fatty acids are highly expressed and provide molecular structural substances for cells, thereby sustaining tumor growth. In previous experiments, researchers cultured cells in a fatty acid-deficient environment and analyzed the growth status of the cells in batches. These studies confirmed that fatty acids play crucial roles in tumorigenesis and have spurred research on targeted regulation for tumor therapy. However, traditional cellular and molecular experiments have certain limitations, making it difficult to resolve the key issue of metabolic heterogeneity among different subpopulations of tumor cells. This limitation has contributed to the failure of targeted therapies to achieve long-lasting therapeutic effects in the treatment of some solid tumors. In contrast, single-cell RNA sequencing (scRNA-seq) technology can analyze gene expression profiles at the single-cell level, overcoming the constraints of traditional methods, and has thus been widely applied in research on tumor metabolism. This technology can accurately identify tumor cell subpopulations with specific phenotypes (such as cancer cell subpopulations with high expression of fatty acid synthase and radiotherapy-resistant glioblastoma cell subpopulations dependent on fatty acid oxidation), clarify the remodeling effects of metabolic heterogeneity on the tumor microenvironment, and provide a detailed molecular mechanism basis for research on targeted tumor therapy. Consequently, it can effectively address the problem of metabolic heterogeneity in tumor cells. In the future, we can integrate scRNA-seq with technologies such as lipidomics and spatial transcriptomics to promote its clinical translation, guide personalized targeted therapy, and provide a precise and efficient new strategy for metabolic targeted therapy in tumors.
Single-cell RNA sequencing technology; Fatty acids; Metabolic heterogeneity; Cancer; Targeted therapy
Effectiveness of Dietary Interventions on Metabolic Profile and Hormonal Profiles in Women with Polycystic Ovary Syndrome (PCOS): A Systematic Review Study
Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age, characterized by insulin resistance, visceral fat accumulation, dyslipidemia, and hyperandrogenism. The combination of metabolic and hormonal disorders worsens reproductive function, increases the risk of cardiometabolic disease, and decreases quality of life. Dietary interventions have become a promising non-pharmacological strategy for improving metabolic and hormonal regulation in PCOS patients. This systematic review was prepared following the guidelines of PRISMA 2020. Literature searches were conducted on PubMed, ScienceDirect, and the Cochrane Library until August 2025. Inclusion criteria included randomized controlled trials (RCTs) in PCOS women with a BMI ≥ 25 kg/m², which evaluated the effects of dietary interventions on metabolic and hormonal profiles. Of the 437 articles screened, seven studies (n = 406 participants) met the eligibility criteria and were critically analyzed. A review of seven RCT studies showed that dietary interventions such as ketogenic, VLCKD, Mediterranean, and low-calorie diets had a positive impact on metabolic and hormonal profiles in women with PCOS. The combination of licorice + a low-calorie diet is effective in lowering insulin resistance while the PMCD diet is more effective in lowering LDL and TG. Hormonal improvements were reflected in increased SHBG (p = 0.042) and decreased LH (p < 0.05), especially in PMCD and ketogenic diets. The low-AGEs diet also helps with weight loss, waist circumference, and HOMA-IR, although data are still limited. The KEMEPHY diet and Low-AGEs showed that both diets had a significant impact on VAT and VFL (p<0.005), with only two studies explicitly describing these outcomes, so more research is needed. Dietary interventions are effective in lowering metabolic profiles, balancing hormonal regulation, and having a positive impact on visceral fat, in women with PCOS. KD and VLCKD are the most promising strategies, while PMCD and low-AGEs diets are beneficial for specific metabolic phenotypes. The principle of personal nutrition needs to be prioritized, although long-term clinical trials are still needed to confirm the effects on reproductive outcomes.
Cognitive Flexibility and Coping Skills as Predictors of Academic Resilience in Children with ADHD
Children with Attention-Deficit/Hyperactivity Disorder (ADHD) face continuous challenges in maintaining attention, regulating impulses, and managing emotions, which often affects their academic engagement and performance. Recent research emphasizes academic resilience—the capacity to recover and remain motivated despite difficulties—as a vital factor for academic success in ADHD populations. This review synthesizes empirical findings on two core predictors of academic resilience: cognitive flexibility and coping skills. Cognitive flexibility enables children to shift perspectives and adapt strategies in response to challenges, while coping skills transform these cognitive adjustments into sustained behavioral and emotional regulation. The review integrates evidence from global and emerging studies, highlighting that these constructs are malleable through intervention. Training programs that strengthen flexibility and coping, when combined with pharmacological or environmental supports, can significantly enhance resilience in children with ADHD. Future research should adopt longitudinal and neurocognitive approaches to clarify developmental mechanisms and optimize intervention design.
Data-Driven Predictive Analytics Framework for Combating Antibiotic Resistance through AI-Enabled Drug Discovery and Surveillance
Antibiotic resistance (AR) has become a pressing concern to the world at large. This has been the case as a proactive strategy can now only be achieved through the use of intelligent solutions toward curbing AR. Research has shown that the development of antibiotics has been hampered by the long drug development process. Moreover, the increase in resistance among microbes has been faster compared to the development of effective antibiotics. This researcher introduces a Data-Driven Predictive Analytics Framework. This has been based on Manik et al. (2018-2023), as the researcher has used AI solutions for the development of medications. This has progressed from drug development to the usage of analytics for chronic and neurological disorders. This has finally led to the development of the Data-Driven Predictive Analysis Framework. This will consist of four aspects: (1) the development of data from multiple sources including genomics and phenomics. This will also involve the usage of the environment. (2) This study will apply analytics solutions to predict the development of AR. (3) AI solutions will also incorporate solutions to develop medications. This has been the final aspect as the researcher concludes the drug development framework. (4) This will involve the development of solutions across the world. This has been the case as the world has been suffering due to the lack of effective antibiotic development. This has been based on the CDC as well as WHO guidelines.
Antibiotic resistance, predictive analytics, AI-enabled drug discovery, big data, multi-omics, surveillance, machine learning.
Spontaneous Coronary Artery Dissection in a Young Female: A Rare Cardiac Catastrophe Without Traditional Risk Factors
Spontaneous coronary artery dissection (SCAD) is an uncommon cause of acute coronary syndrome, predominantly affecting young women without traditional cardiovascular risk factors. We report a 32-year-old female who presented with sudden-onset, severe retrosternal chest pain radiating to the left arm, associated with diaphoresis and mild dyspnea. She had no history of hypertension, diabetes, dyslipidemia, smoking, or family history of premature coronary artery disease. Initial evaluation revealed subtle ST-segment changes on electrocardiogram and modestly elevated high-sensitivity troponin I levels. Coronary angiography demonstrated a type 2 SCAD of the mid-left anterior descending artery, confirmed by intracoronary imaging showing an intramural hematoma with preserved distal flow. Laboratory workup, echocardiography, and computed tomography angiography for extracoronary vascular assessment were unremarkable. Given hemodynamic stability and maintained coronary perfusion, the patient was managed conservatively with dual antiplatelet therapy, beta-blockers, and close monitoring, with plans for follow-up imaging to assess vascular healing. This case underscores the importance of considering SCAD in young women presenting with acute chest pain, highlights the critical role of coronary imaging in diagnosis, and demonstrates that tailored conservative management can lead to favorable outcomes while avoiding unnecessary interventions.
Spontaneous coronary artery dissection, SCAD, acute coronary syndrome, young female, intramural hematoma, conservative management, coronary angiography, non-atherosclerotic coronary disease, cardiac emergency, chest pain.
Unmasking Connective Tissue Disease Through Pulmonary Hypertension: A Diagnostic Challenge
Pulmonary arterial hypertension (PAH) is a severe and potentially life-threatening manifestation of connective tissue diseases, often presenting insidiously and complicating timely diagnosis. We report the case of a 48-year-old Saudi woman with no prior chronic illness who presented with progressive exertional dyspnea and fatigue over six weeks. Examination revealed mild central cyanosis, elevated jugular venous pressure, and a prominent right ventricular heave. Laboratory evaluation showed elevated NT-proBNP and mild hypoxemia, while echocardiography demonstrated right ventricular dilation and an estimated pulmonary artery systolic pressure of 70 mmHg. Right heart catheterization confirmed pre-capillary pulmonary hypertension. Serologic workup revealed high-titer anti-U1 RNP antibodies, ANA positivity, and features consistent with mixed connective tissue disease (MCTD), with no evidence of left heart disease, thromboembolic disease, or significant interstitial lung involvement. Management included combination PAH-targeted therapy with an endothelin receptor antagonist and a phosphodiesterase-5 inhibitor, alongside low-dose corticosteroid immunosuppression. Supportive care comprised oxygen supplementation and close hemodynamic monitoring. Over three months, the patient’s functional status improved from WHO functional class III to II, with reduction in NT-proBNP and increased six-minute walk distance. This case underscores the diagnostic challenge of MCTD presenting primarily with PAH, emphasizing that subtle systemic features may precede cardiovascular compromise. Early recognition, prompt hemodynamic assessment, and a multidisciplinary management strategy are crucial to improve prognosis and prevent irreversible right ventricular dysfunction. Clinicians should maintain a high index of suspicion for PAH in patients with connective tissue disease, even in the absence of overt systemic manifestations.
Pulmonary hypertension, connective tissue disease, autoimmune disease, interstitial lung disease, systemic sclerosis, vasculopathy, diagnostic challenge, and pulmonary vascular disease.
Recurring Abdominal Pain: The Hidden Clue of Antiphospholipid Syndrome
Recurrent abdominal pain is a common clinical presentation, yet when episodes are severe, episodic, and unexplained by routine gastrointestinal investigations, vascular etiologies must be considered. We present a 52-year-old previously healthy man with a six-week history of intermittent, severe central abdominal pain, culminating in an acute exacerbation. Prior evaluations, including ultrasound, non-contrast CT, and endoscopy, were unrevealing. On acute presentation, laboratory studies demonstrated elevated D-dimer and mild lactate elevation, prompting contrast-enhanced CT angiography, which revealed a proximal superior mesenteric artery thrombus with preserved bowel viability. Further workup confirmed triple-positive antiphospholipid syndrome (APS), establishing the underlying prothrombotic etiology. The patient underwent urgent systemic anticoagulation with unfractionated heparin followed by successful endovascular thrombectomy and catheter-directed thrombolysis. He was subsequently transitioned to long-term warfarin therapy with multidisciplinary follow-up. This case highlights the protean manifestations of APS, demonstrating that recurrent, transient mesenteric ischemia may precede catastrophic arterial thrombosis. Early recognition, prompt vascular imaging, and tailored anticoagulation—combined with minimally invasive revascularization when feasible—are pivotal in preventing bowel infarction and optimizing outcomes. Clinicians should maintain high suspicion for APS in atypical thrombotic presentations beyond the classic venous or cerebrovascular events.
Abdominal Pain, Antiphospholipid Syndrome, Thrombophilia, Mesenteric Ischemia, Arterial Thrombosis, Lupus Anticoagulant, Anticardiolipin, AntiB2-Glycoprotein I, Anticoagulation, Thrombosis, Small Bowel Infarction.
Gut Warning: Acute Mesenteric Ischemia as The First Sign of Hidden Atrial Fibrillation
Some surgical abdomens may present with severe pain that appears disproportionate to physical examination findings, a red flag that clinicians must not overlook, as early mucosal ischemia can progress to transmural necrosis and eventual signs of peritonitis. Atrial fibrillation may remain clinically silent until it manifests through a first embolic event, as illustrated in this case. This report highlights the life-saving value of maintaining a low threshold for abdominal CT angiography in patients with atrial fibrillation. We present a 64-year-old male who arrived with acute, severe abdominal pain of sudden onset, persisting for approximately five hours prior to hospital admission. Laboratory findings of leukocytosis and lactic acidosis indicated acute intestinal injury and early tissue hypoxia, prompting a high index of suspicion for acute mesenteric ischemia which was later confirmed by CT angiography of the abdomen. Initial management included intravenous fluids, broad-spectrum antibiotics, rate control, analgesia, and gastrointestinal decompression, followed by definitive treatment via endovascular embolectomy. The patient demonstrated an excellent recovery, with postoperative angiography confirming successful reperfusion, and was discharged after an uncomplicated ICU course on long-term anticoagulation therapy.
Advancing U.S. Healthcare with LLM–Diffusion Hybrid Models for Synthetic Skin Image Generation and Dermatological AI
The integration of large language models (LLMs) with diffusion-based generative architectures has redefined the boundaries of medical image synthesis, particularly in dermatological diagnostics. This study presents a novel hybrid model for synthetic skin image generation, leveraging the textual understanding capabilities of LLMs and the generative precision of diffusion models. The dataset was derived from the UCI Skin Segmentation Dataset, consisting of high-resolution dermal samples categorized into skin and non-skin classes. Following extensive preprocessing and feature extraction, semantic conditioning through LLMs was applied to guide the diffusion process, resulting in highly realistic and clinically relevant synthetic skin images. Experimental results demonstrate superior performance compared to traditional GANs and autoencoder-based models, achieving a Structural Similarity Index (SSIM) of 0.982, PSNR of 38.7 dB, and FID score of 5.43, indicating exceptional image fidelity and diversity. The proposed model also facilitates data augmentation for machine learning models in dermatology, enhancing classification accuracy by 7.5% on average. Beyond academic relevance, the implementation of this hybrid architecture holds immense potential for U.S. healthcare applications, enabling scalable skin disease datasets, supporting dermatological AI training, and improving diagnostic precision in rural and underserved communities.
Synthetic skin image generation, diffusion model, large language model (LLM), medical image synthesis, dermatology AI, generative models, healthcare innovation
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc/4.0
Complications of the Patient with Hemophilia Associated with Transfusion of Blood Components or Derivatives: 35 Cases
Hemophilia is a congenital bleeding disorder characterized by deficient or absent clotting factors, most commonly Factor VIII (Hemophilia A) or Factor IX (Hemophilia B). Regular transfusions of blood products, such as clotting factor concentrates and plasma derivatives, are essential in managing bleeding episodes in hemophilic patients. However, transfusion therapy is not without risks. This study aims to explore the complications associated with blood component transfusion in 35 hemophilic patients, analyzing a range of adverse events that arose following transfusion therapy. The study retrospectively reviewed the medical records of 35 hemophilic patients who received blood component transfusions over a 2-years period. Data were collected on the type of transfused products, the number of transfusions, and the complications encountered. These complications included allergic reactions, the development of inhibitors (antibodies against transfused clotting factors), viral infections (such as hepatitis and HIV), iron overload, and thrombotic events. A total of 35 hemophilic patients (27 male, 8 female) participated in this study. The mean age was 34.2 years, with a range spanning from 8 to 68 years. Hemophilia A (n = 22, 62.9%) was more common than Hemophilia B (n = 13, 37.1%). The severity of hemophilia was categorized as severe (n = 15, 42.9%), moderate (n = 12, 34.3%), and mild (n = 8, 22.8%). The mean number of transfusions per patient was 10.3, with clotting factor concentrates being the most frequently used transfusion product (n = 29, 82.9%). The study revealed a 34% complication rate (n = 12). The most common complications were allergic reactions (14.3%), inhibitor development (20%), and iron overload (11.4%). Thrombotic events were less frequent (5.7%), while one case of hepatitis B (2.9%) was noted, which was attributed to older plasma-derived factor products. Statistical analysis showed a significant correlation between severe hemophilia and inhibitor development (71% of severe cases developed inhibitors, p < 0.05). No significant association was observed between transfusion product type and the occurrence of complications. The study highlights the need for careful monitoring and management of hemophilic patients receiving transfusions. Strategies to minimize risks, such as the use of recombinant clotting factors, individualized transfusion protocols, and regular screening for inhibitors, are critical in improving patient outcomes and reducing complications.
Hemophilia, Blood Transfusion, Clotting Factor Concentrates, Plasma Derivatives, Transfusion Complications, Inhibitor Development