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104 articles for “Medical Decision Making”
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Review on Machine Learning Techniques for Heart Failure Analysis in Health Industries
Abstract: There are few bodily components as crucial as the heart. It aids in the filtration and distribution of blood to every area of a body. The world's biggest cause of death is heart disease. It has been reported that symptoms include breathing difficulties, fast heartbeat, and chest discomfort. They analyze this data on a regular basis. This review begins with a brief introduction of cardiac disease and the present methods …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 29–43 Read article
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Protagonist of Aspirin in Primary Treatment of Cardiovascular Disease: An Overview
Abstract: AbstractAspirin (ASA) is the most used medication on the globe. The benefits of aspirin therapy for the secondary prevention of cardiovascular disease clearly outweigh the risks of bleeding, and low- dose aspirin is uniformly recommended in this condition. While the clinical use of aspirin in secondary cardiovascular disease (CVD) prevention remains undisputed, its role in primary prevention is controversial. Recently, three trials of primary prevention reported neutral net benefit results …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 9, Issue 2, 2020 · pp. 12–30 Read article
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Advances in Trauma Surgery: Innovations, Historical Perspectives, and Future Directions in Patient Care
Abstract: Trauma care has evolved significantly over the past few decades, with innovations in surgical techniques, medical devices, and procedural protocols enhancing the outcomes for patients experiencing life-threatening injuries. This article explores recent surgical innovations in trauma care, focusing on advancements in hemorrhage control, rapid trauma intervention, and the use of novel technologies to improve surgical precision and recovery. Key developments such as hemostatic agents, minimally invasive techniques, and the integration …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 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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Transforming Digital Health Card Healthcare in India: An Integrated IT Solution
Abstract: India's healthcare sector faces critical challenges, including fragmented medical records, limited access to quality care in rural areas, and inefficiencies in patient engagement and insurance processes. This study proposes an innovative IT-driven healthcare model integrating a digital health card, web application, and NFC-enabled mobile platform. The system aims to streamline medical record management, enable telemedicine consultations, and provide seamless prescription and insurance integration. Advanced digital capabilities ranging from AI-driven recommendations …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 11–15 Read article
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A Study on The Impact of Artificial Intelligence in Pharmaceuticals
Abstract: The main goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem-solving, and decision-making. AI is becoming more and more significant in several pharmacy domains, including polypharmacology, hospital pharmacy, drug discovery, and drug delivery formulation development. Various types of artificial neural networks (ANNs), including deep neural networks (DNNs) and recurrent neural networks (RNNs), are utilized in the development of drug delivery formulations and in drug …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 24–32 Read article
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GenChrome-ML: A Machine Learning Framework for Early Detection of Chromosomal Disorders Using Genomic Data
Abstract: The increasing burden of chronic disease and cancer demands innovative, more rapid and effective diagnostic tools in the field of healthcare. The majority of current diagnostic tools are dependent upon clinical symptomology and manual evaluation, leading to delays in early detection and treatment. The development of artificial intelligence (AI) and machine learning (ML), in recent years, has offered opportunities for the enhancement of disease prediction, diagnosis and personalization of treatment …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Brain Stroke Detection Using Deep Learning and Grad-CAM Explainability Framework
Abstract: Seconds matter when a brain stroke occurs; it is a race against time where rapid, precise intervention is the only way to preserve a patient’s quality of life. This research introduces a deep learning framework designed to act as a vital ally for clinicians, providing automated, high-speed stroke detection through brain MRI analysis. At the heart of our approach is EfficientNetB0, a sophisticated neural network chosen for its ability to …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 8–14 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1109–1134 Read article
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GeneXpert MTB/RIF Assay (PCR Mycobacterium Tuberculosis): A Revolution in Management of Tuberculosis
Abstract: Background: Workup of pulmonary tuberculosis depends upon sputum microscopy. Sputum microscopy is less sensitive, human resource dependent and time consuming. Sometimes, it lead us to a delay in the diagnosis and may result in the spread of the disease. This seriously disturbs TB control program. There is a need for a more sensitive method. Similarly, early detection of rifampicin resistance is also of utmost importance to prevent MDR strains from …
Published in Research and Reviews : A Journal of Immunology · Vol. 8, Issue 2, 2018 · pp. 8–12 Read article
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Smart E-Health Consultation Portal
Abstract: The Smart E-Health Consultation Portal is an e-healthcare application that allows access to high-quality, efficient, and accessible medical care services via remote consultation of doctors & patients. Patients can communicate with their healthcare provider through video, voice, or chat communication which eliminates geographic and temporal boundaries. Factors that influence a patient's perception of satisfaction consist of clear and timely responses from their healthcare provider, a guarantee of privacy when using …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 Read article
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Factors Influencing Institutional Child Birth among Women in Aynalem Kebelle, Mekelle, Tigray, Ethiopia
Abstract: Giving birth is the most critical part of pregnancy intervention for improving maternal and child health in Ethiopia with maternal mortality ratio of 673 per 100,000 live births. The majority of births are delivered at home and the proportion of deliveries assisted by skilled attendant is very low. The present study assessed the factors influencing institutional child birthing among women in Aynalem Kebelle, Mekelle, and Tigray, Ethiopia.A community-based cross-sectional study …
Published in Research and Reviews: A Journal of Medicine · Vol. 6, Issue 2, 2016 · pp. 21–27 Read article
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Optimizing Heart Disease Prediction: Comparative Analysis of Machine Learning Algorithm for Early Detection
Abstract: The expanding realm of data analysis holds considerable importance in healthcare, particularly in the medical sector where forecasting heart disease is considered a complex endeavor. Early prediction of serious health conditions can be the determining factor between survival and fatality, with heart disease being one such critical health issue. Over the past decade, the main reason for death has been heart disease. Heart disorders come in many different forms, and …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 1–10 Read article
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An Evidence Based Analytical Study on Capability of ChatGPT in Advanced AI Based Patient Drug Counseling
Abstract: The application of ChatGPT in providing drug counseling to patients offers the best approach to enhancing policies of healthcare support in decision-making. Aim and Objectives: The present study mainly involves an evaluation of the capability of ChatGPT in the management of drug counseling among patients suffering from various metabolic disorders. Methodology: The present study was a community-based interventional study conducted for a period of 12 months from October 2023 to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 8–13 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Nursing Image and Empowerment: Beyond Professional Conduct
Abstract: The public image of nursing influences someone’s decision to choose the nursing profession, to remain in nursing, to promote nursing, and to progress in nursing. The society undervalued nursing as a profession probably due to its female dominion, suppression of females in the society, and the portrait of nurses as ‘physician’s maid’ in the media. We need to redefine our image around professional attributes such as critical thinking, therapeutic interventions, …
Published in Journal of Nursing Science & Practice · Vol. 9, Issue 3, 2019 · pp. 13–17 Read article
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Polymer-Integrated Smart Biomedical Waste Management System Using AI and Sensor-Based Segregation
Abstract: Biomedical waste, which comes from healthcare facilities like hospitals, clinics, and labs, includes both infectious and non-infectious materials. This can range from sharps and pathological waste to pharmaceutical leftovers and general medical trash. If this waste isn't handled, sorted, and disposed of properly, it can pose serious contamination risks, leading to infections, workplace hazards, environmental damage, and public health emergencies. Traditional biomedical waste management often relies on manual sorting, which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 172–184 Read article