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155 articles for “Clinical data integration”
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Enhancing Nursing Education Through AI-Driven Adaptive Learning Systems
Abstract: The integration of Artificial Intelligence (AI) in nursing education offers significant potential to enhance learning experiences by personalizing education, improving knowledge retention, and developing clinical competencies. This study evaluates the effectiveness of AI-driven adaptive learning systems compared to traditional lecture-based teaching methods in nursing education. A mixed-methods approach was used, with 200 nursing students participating in a quasi-experimental design. The intervention group (100 students) used AI-powered adaptive learning platforms for …
Published in Journal of Nursing Science & Practice · Vol. 15, Issue 2, 2025 · pp. 29–34 Read article
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Today’s Status of Digital Resources in Medical College Libraries
Abstract: Digital resources have become integral to the advancement of medical education and research, enabling access to current scientific evidence, clinical guidelines, e-books, e-journals, and multimedia learning tools. Medical college libraries worldwide are transitioning from traditional print repositories to hybrid digital knowledge hubs. This transformation is driven by the evolution of Information and Communication Technology (ICT), rising expectations of learners and educators, institutional mandates for evidence-based practice, and the diffusion of …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 1, 2026 · pp. 85–94 Read article
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IoT-Enabled Flexible Polymer Sensors for On-Body Health Monitoring and Real-Time Data Transmission
Abstract: Wearable health monitoring systems have grown increasingly vital in shifting care beyond clinical settings, yet many existing technologies remain hamstrung by rigid substrates and unreliable data streaming, impeding continuous and comfortable physiological assessment. Despite advances in flexible materials, most current sensor platforms suffer from limited mechanical endurance, signal instability under dynamic conditions, or an inability to sustain real-time wireless transmission. This work addresses those deficiencies by introducing a fully integrated, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 188–200 Read article
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A Review on Unmasking Merkel Cell Polyomavirus: From Discovery to Cancer Driver
Abstract: Merkel cell polyomavirus (MCPyV) is a small, non-enveloped, circular double-stranded DNA virus belonging to the Polyomaviridae family, first characterized in 2008. Epidemiological data suggest widespread exposure, with seroprevalence rates approaching 80% in adults. While primary infection is typically asymptomatic, rare integration events in Merkel cells can initiate oncogenesis, yielding Merkel cell carcinoma (MCC), a neuroendocrine skin cancer with a five-year survival rate under 60%. This review integrates findings from six …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 6–11 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Blockchain for Secure Health Records in India: Aligning with Ayushman Bharat
Abstract: India’s healthcare ecosystem continues to face significant hurdles, particularly in the efficient management, protection, and accessibility of patient health records. For decades, medical data in the country has remained scattered across institutions, recorded in incompatible formats, and stored in systems that rarely communicate with each other. These gaps not only slow down clinical decision-making but also increase exposure to data breaches and other cybersecurity risks. In this context, blockchain technology …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 01–05 Read article
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Biomarkers in Cancer Research: Discovery and Future Directions
Abstract: Biomarkers have transformed the study of cancer, providing critical information regarding prognosis and therapy response and promoting earlier diagnosis. This paper discusses the different parts of cancer biomarkers, starting with their description, classification, and major types, which are the groundwork for understanding their clinical role. The discussion on the development and validation process of biomarkers is then undertaken, focusing on state-of-the-art techniques and the importance of ensuring accuracy and reproducibility. …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 22–26 Read article
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Revolutionizing Artificial Organs: Next-Generation Membrane Technologies for Precision Medicine and Global Health
Abstract: Membrane technology has emerged as a cornerstone in the advancement of artificial organ systems, offering critical functionalities in selective molecular filtration, tissue scaffolding, and controlled therapeutic delivery. Recent innovations have propelled the field beyond traditional polymeric membranes to include nanostructured, biomimetic, and stimuli-responsive materials, significantly enhancing biocompatibility, selectivity, and durability. The integration of smart technologies, such as AI-driven membrane design, bioelectronic sensors, and personalized fabrication via 3D printing, is ushering …
Published in International Journal of Membranes · Vol. 2, Issue 2, 2025 · pp. 29–39 Read article
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Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 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 · pp. 10–20 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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A Literature Review on Future Perspective of Metformin use for Chemotherapy
Abstract: The emergence of metformin as a potential anticancer and cancer-preventive therapeutic tool is exciting. More recently, metformin has been associated with decreased cancer incidence and mortality in diabetic patients and the insulin-lowering effects of metformin are integral to its anticancer properties. With the added benefits of being readily available, economical, and easily tolerated with good safety profile, it can be effortlessly transitioned from bench to bedside for cancer therapy. So, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 9, Issue 3, 2020 · pp. 1–9 Read article
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A Systematic Review on Factors Contributing to Infertility
Abstract: Infertility is a multifactorial reproductive health condition affecting approximately 10–15% of couples worldwide and continues to represent a major clinical and social challenge. Despite substantial advances in assisted reproductive technologies, diagnostic methods, and therapeutic interventions, many couples still face difficulties in achieving pregnancy. The impact of infertility extends beyond physical health, often leading to emotional distress, social pressure, and financial burdens, especially in societies where parenthood is highly valued. Consequently, …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 1, 2026 · pp. 31–35 Read article
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Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
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The Concept of Guillain-Barré Syndrome (GBS) in Unani Medicine and the Potential Role of Unani Pharmacology in Its Management
Abstract: Introduction: Guillain–Barré Syndrome (GBS) is an autoimmune neurological disorder characterized by progressive muscle weakness and paralysis due to immune-mediated damage to the peripheral nervous system. Conventional treatments focus on immunotherapy and supportive care, but alternative approaches, such as Unani Medicine offer promising holistic management strategies. Unani Medicine attributes GBS to humoral imbalance, particularly an excess of Balgham (Phlegm) affecting nerve function, leading to weakness and dysfunction. Objective: This study aims …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 32–52 Read article
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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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The Role of AI in Modern Healthcare Systems
Abstract: In the Indian pandemic, several issues in the healthcare system have brought to the forefront the imperative of hospitals shifting from manual medical records to computerized healthcare information systems. These solutions offer an effective method for integrating computer-based decision support tools and communicating e-healthcare information. With increasing dependence on AI-based solutions, a strong IT infrastructure is essential for improving healthcare quality, data security, and controlling increasing medical expenses. Advances in …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 69–76 Read article
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Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
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Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
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Psychological Profile of Patients Undergoing Hemodialysis and Its Association with Physiological Parameters
Abstract: Background: End-stage renal disease (ESRD) is a chronic, progressive condition requiring maintenance hemodialysis, which imposes substantial physiological, psychological, and social burdens on patients. While physiological indicators are routinely monitored during treatment, the influence of psychological factors on these indicators and patients' quality of life remains inadequately explored, particularly in the Indian context. Objective: To investigate the relationship between psychological variables (depression, anxiety, illness intrusiveness, and quality of life) and physiological …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 2, 2026 · pp. 40–48 Read article