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13 articles for “Patient stratification”
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Neuroimaging in Clinical Trials for Huntington’s Disease: Emerging Research Findings: The Advancement Directions and Implications
Abstract: Neuroimaging is very important in coordinating and conducting Huntington’s disease clinical trials as a tool in selecting patients, managing safety concerns, and assessing the benefits of interventions. This review presents the current uses and potential future uses of structural and functional magnetic resonance imaging (MRI), diffusion imaging, positron emission tomography (PET), proton magnetic resonance spectroscopy (MRS), perfusion imaging, and magneto encephalography (MEG) in HD trials. We describe how these modalities …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 32–44 Read article
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Metabolites in Modern Medicine: Decoding the Future of Health and Diseases
Abstract: The end products of many metabolic processes in cells are called metabolites. Each reaction contributes a specific metabolite. Metabolites act as fingerprints of on-going biological processes. Constant changes in cellular composition due to both environmental and internal factors. By analysing the types and presence of metabolites, scientists can effectively reconstruct the inner workings of a cell or organism. In the past, analysing metabolites was a slow and tedious process, often …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 2, 2024 · pp. 1–13 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Extracellular Vesicle-Based Liquid Biopsies: Decoding the Tumor Microenvironment for Precision Oncology
Abstract: The tumor microenvironment (TME) plays a pivotal role in cancer initiation, progression, and therapeutic response. Decoding the TME is, therefore, essential for advancing precision oncology. Extracellular vesicles (EVs), including exosomes and microvesicles, are nanoscale lipid bilayer particles secreted by tumor and stromal cells. They transport a wide range of bioactive molecules, such as DNA, RNA, proteins, lipids, and metabolites, which reflect the dynamic state of the TME. Recent advances in …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 1, 2026 · pp. 43–62 Read article
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Comparison of Several Clinical Scoring Systems in Predicting the Outcome of Variceal Bleeding
Abstract: Background: Stratification of variceal bleeding patients into high-risk and low-risk group is very important to guide them through the suitable clinical pathway and to save the medical costs. We purposed to find out the best scoring system in the prediction of rebleeding and death after variceal bleeding by comparing four clinical scoring systems(clinical Rockall score, complete Rockall score, AIMS65 score, Child-Pugh score) which seemed to be applicable and simple. Method: …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 2, 2025 Read article
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Red Cell Distribution in Pregnancy Associated with Preeclampsia Patients in Worldwide: A Brief Review
Abstract: Introduction: Preeclampsia (PE) is a major obstetric problem contributing considerably to maternal and prenatal morbidity and mortality worldwide. Preeclampsia varies in incidence in India from 5% to 15%. The role of this hematological parameter in clinical assessment, differential diagnosis, and prognosis evaluation of PE remains unclear. Thus, the purpose of the current review was to investigate the red cell distribution width (RDW) in preeclampsia, analyze its importance for early diagnosis, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 1, 2024 · pp. 6–12 Read article
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Navigating the Principles and Practice of Oral Anticoagulant Therapy: A Comprehensive Healthcare Guide
Abstract: Oral anticoagulant therapy plays a critical role in the prevention and treatment of thromboembolic disorders, including atrial fibrillation (AF), venous thromboembolism (VTE), and mechanical heart valve replacement. This research article aims to provide a comprehensive overview of the principles and practice of oral anticoagulant therapy, focusing on the mechanisms of action, pharmacokinetics, clinical indications, monitoring, and management of associated complications. The cornerstone of oral anticoagulant therapy includes vitamin K antagonists …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 76–82 Read article
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Assessing the Increasing Incidence of Prostate Cancer in Urban Delhi: Risk Factors, Early Detection, and Treatment Challenges
Abstract: Background: Prostate cancer has emerged as the second most prevalent cancer among men in India, with rapidly increasing incidence rates in urban areas like Delhi. This rise is attributed to urbanization, lifestyle changes (high-fat diets, tobacco use, sedentary behavior), increased life expectancy, and improved diagnostics. Despite its growing burden, low awareness, limited screening programs, and treatment barriers hinder early detection and effective management. This study examines the epidemiological trends, risk …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 21–28 Read article
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Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
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The Importance of Self-Care for Healthcare Professionals in North India: A Regional Analysis of Burnout, Resilience and Institutional Support
Abstract: Background: Burnout in healthcare professionals is described using the framework of Occupational Health and Resilience Theory, where self-care is an individual-level coping mechanism and institutional support is an organizational-level moderator. However, there is a lack of regional data from North India on the structural and contextual factors influencing burnout. Healthcare workers (HCWs) in North India face mounting pressures due to high patient loads, limited mental health resources, and overlapping professional …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article