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155 articles for “Clinical data integration”
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Path Lab-AI: An Autonomous Framework for Error-Free Histopathology Slide Interpretation
Abstract: Path Lab-AI represents a fully autonomous platform for the analysis of histopathology slides with circumscribed structures, designed to obtain highly accurate results using diagnostic methods and avoiding the usual limitations of standard microscopy-based pathology. Leveraging recent deep learning and whole slide image (WSI) analysis innovations, our system takes advantage of automated WSI ingestion along with pre-processing steps to account for staining variability, remove artifacts, and localize tissue from background. Such …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 19–30 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article
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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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MedVerse AI: An Intelligent Digital Health Platform for Patient-Centric Healthcare and Proactive Disease Prediction
Abstract: The rapid digitization of healthcare has led to an unprecedented growth in medical data, ranging from diagnostic images and laboratory reports to electronic health records and clinical notes. Despite this abundance, patients and healthcare providers often struggle to extract meaningful insights due to data complexity and fragmentation. MedVerse AI proposes an intelligent digital health platform that unifies medical image analysis, clinical report interpretation, real-time interaction, and predictive disease analytics into …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 2, 2026 · pp. 1–7 Read article
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Leveraging Genome-Wide Association Studies for Precision Medicine in Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) are the leading cause of death globally, with complex etiologies involving genetic, environmental, and lifestyle factors. Genome-wide association studies (GWAS) have significantly advanced the understanding of genetic underpinnings of CVDs by identifying numerous risk loci and variants associated with various cardiovascular conditions. This review explores the potential of GWAS to drive precision medicine in cardiovascular diseases by linking genetic data with clinical outcomes, providing insights into disease …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 35–39 Read article
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Collaborative Care for Diabetic Retinopathy: Integrating Artificial Intelligence and Clinical Pharmacy Services - A Comprehensive Review
Abstract: Background: Diabetic retinopathy (DR) remains the leading cause of blindness among working-age adults globally, affecting approximately 103 million people worldwide. The integration of artificial intelligence (AI) technologies with clinical pharmacy services presents unprecedented opportunities to enhance screening, diagnosis, and management of DR through collaborative care models. Objective: This comprehensive review examines the current landscape of collaborative care approaches for diabetic retinopathy management, focusing on the integration of AI-powered diagnostic tools …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 118–128 Read article
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Phytotherapeutic Potential of Melaleuca: An Integrative Review of Phytochemistry and Antimicrobial, Antifungal, Antioxidant, and Antiviral Mechanisms
Abstract: Melaleuca alternifolia and other species of the Melaleuca genus stand out for the broad spectrum of pharmacological properties attributed to their bioactive compounds, such as monoterpenes, sesquiterpenes, flavonoids, and polyphenols. This study aimed to critically review and analyze scientific evidence produced between 2005 and 2025 regarding the antimicrobial, antifungal, antioxidant, and antiviral activities of Melaleuca, correlating its phytochemistry with molecular mechanisms of action. For this purpose, an integrative literature review …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 Read article
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Phytotherapeutic Potential of Melaleuca: An Integrative Review of Phytochemistry and Antimicrobial, Antifungal, Antioxidant, and Antiviral Mechanisms
Abstract: Melaleuca alternifolia and other species of the Melaleuca genus stand out for the broad spectrum of pharmacological properties attributed to their bioactive compounds, such as monoterpenes, sesquiterpenes, flavonoids, and polyphenols. This study aimed to critically review and analyze scientific evidence produced between 2005 and 2025 regarding the antimicrobial, antifungal, antioxidant, and antiviral activities of Melaleuca, correlating its phytochemistry with molecular mechanisms of action. For this purpose, an integrative literature review …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 · pp. 16–30 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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A Hybrid Machine Learning Approach for Enhanced Patient Diagnosis and Health Outcome Prediction
Abstract: Rapid and accurate diagnosis is essential to present day practitioners of medicine, yet can be complicated by the enormous volume and complexity inherent in clinical data. To this end, we here propose a hybrid machine learning model in combination with Recursive Feature Elimination (RFE) and ensemble voting to enhance the diagnostic accuracy by integrating multiple models. Trained on real-world electronic health data, including lab results, demographics and medical history, the …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Advances in Simulation and Surgical Skill Training Evolution: Narrative Integrative Review
Abstract: Simulation-based education has emerged as a cornerstone of contemporary general surgery training, driven by increasing emphasis on patient safety, competency-based education, and rapid technological innovation. Traditional apprenticeship models, while foundational, are constrained by reduced operative exposure, work-hour limitations, and variability in clinical case mix. In this context, simulation provides a structured, reproducible, and safe environment for acquisition, assessment, and refinement of surgical skills across the training continuum. This narrative review …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–13 Read article
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Interpretable Skin Cancer Detection via Optimized CNN Models for Smart Healthcare Solutions
Abstract: Skin cancer is a common and potentially life-threatening condition, highlighting the importance of reliable and efficient diagnostic techniques. Recently, convolutional neural networks (CNNs) have demonstrated significant potential in automating the classification of skin cancer using thermoscopic images. Despite these advancements, the lack of interpretability in these models poses a barrier to their widespread use in clinical settings. In this study, we propose an interpretable CNN architecture optimized for skin cancer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 41–45 Read article
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Advanced Security Mechanisms for Protecting Mobile Devices: A Comprehensive Analysis of Threats and Counter Measures
Abstract: The digitization of clinical care has led to significant advancements in medical devices and telemetry, fundamentally transforming the healthcare landscape. These innovations have enhanced the quality of patient care by enabling more accurate diagnoses, real-time monitoring, remote consultations, and increased transparency in clinical workflows. As a result, modern medical practices have become more efficient, data-driven, and patient-centric. Devices such as infusion pumps, pacemakers, ventilators, and wearable monitors now rely heavily …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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Navigating the Horizon: Current Trends in Elevating Quality Assurance in Clinical Research
Abstract: The landscape of clinical research quality management has evolved significantly in recent years, driven by stringent regulatory frameworks and globalization of trials. This evolution underscores the importance of integrating quality into all aspects of the clinical trial process from design to postresearch activities. Concepts such as Good Clinical Practice (GCP) and Quality by Design (QbD) are central to ensuring the reliability and accuracy of trial data while safeguarding patient safety …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 1, 2024 · pp. 1–8 Read article
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Modernizing Pharmacovigilance: Leveraging AI,Automation, and Real-World Data for Drug Safety
Abstract: Pharmacovigilance, or PV, is “the pharmacological science relating to the detection, assessment, understanding, and prevention of adverse effects, mainly long term and short-term adverse effects of medicines.” PV’s specific objectives are to increase patient care and safety when using medications and all medical and paramedical therapies; assist in evaluating the benefits, drawbacks, efficacy, and risks of medications, ensuring their safe, prudent, and more effective use; and promote clinical training, education, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 21–30 Read article
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Signal Drift Compensation in Polymer-Based Wearable Biosensors Using Data Processing Techniques
Abstract: Polymer-based wearable biosensors have emerged as promising platforms for continuous physiological monitoring due to their mechanical flexibility, low operating voltage, and compatibility with soft biological interfaces. However, their long-term deployment remains challenging because of signal drift caused by polymer ageing, hydration–dehydration cycles, ionic trapping, and environmental variations. These effects introduce baseline fluctuations and sensitivity degradation, which compromise the reliability and interpretability of physiological measurements. This study proposes a data-processing–driven framework …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 197–207 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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A Standards-Compliant API Framework for Integrating NAMASTE and ICD-11 TM2 Terminologies into Indian Electronic Medical Records (EMRs)
Abstract: The lack of standardized, interoperable terminology services has hindered the integration of India’s traditional medical systems into the mainstream digital health infrastructure. Although ICD-11 Traditional Medicine Module 2 (TM2) offers an internationally harmonized classification for traditional medicine diagnoses and the NAMASTE portal defines structured vocabularies for AYUSH conditions, current Electronic Medical Record (EMR) platforms in India are unable to natively consume, map, or translate these terminologies in a way that …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 · pp. 19–27 Read article
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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 Read article
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AI in Healthcare: Drug Delivery in Tuberculosis
Abstract: Tuberculosis (TB) , mainly caused by Mycobacterium tuberculosis, remains a major global health burden, accounting for millions of new infections and deaths each year. Although progress has been made in diagnosis and treatment, the growing threat of multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB makes disease control increasingly difficult. Conventional diagnostic approaches such as chest X-rays, sputum smear microscopy, and culture methods continue to play an important role, but they …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 9–17 Read article