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211 articles for “medical machine learning”
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Role of Artificial Intelligence in Structural Health Monitoring-A Brief Evaluation
Abstract: Artificial intelligence (AI) refers to the capacity of a machine or a computer to ‘think’ or reason in the way a human would, utilizing experience, learned facts, and flexible rules to solve problems that may not fit the standard outlines for a normal algorithm. From this follows the utilization of AI in various sectors, such as the information technology (IT) industry, media, healthcare and medicine, logistics, environmental sustainability, finance, business, …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 34–39 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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Data Breaches and Malware Detection in Healthcare System
Abstract: The healthcare sector is undergoing a chaotic digital transformation, but the incorporation of new technologies is not typically the cause of health information-related data breaches. According to published industry studies, there are still many recorded data breaches as a result of equipment theft, hacking, ransomware attacks, and misuse, as well as a lack of basic security precautions. When compared to any other field, protecting health information is given the highest …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 15–24 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Digital Twins in Human Anatomy and Physiology Education: Current Status and Future Perspectives
Abstract: Digital Twin (DT) technology has emerged as a promising innovation in healthcare by creating dynamic virtual representations of physical systems through the integration of artificial intelligence (AI), computational modeling, real-time data, and advanced visualization technologies. Although DTs have been widely investigated in precision medicine and clinical decision-making, their application in Human Anatomy and Physiology (HAP) education remains in its early stages. This review aims to examine the current status, educational …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 3, 2026 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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HabituraX: A Comprehensive Machine Learning System for Lifestyle-Based Disease Risk Prediction
Abstract: The increased prevalence of lifestyle-related non-communicable diseases such as diabetes, obesity, and sleep disorders in the world requires the development of proactive risk-stratification tools. Recent studies indicate that there is a significant shift in favor of multimodal artificial intelligence (AI) models that comprise deep learning models such as CNNs and LSTMs, which often demonstrate high predictive accuracy, along with complex ensemble approaches. However, the necessary clinical interpretability to perform open …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 2, 2026 · pp. 12–23 Read article
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AI-Powered ECG Prediction System for Detecting Cardiovascular Disease
Abstract: The proposed AI-powered CardioSmart Analyzer, an electrocardiogram (ECG) prediction system, presents an innovative and scientifically rigorous approach to the real-time automated analysis of ECG signals for diagnosing various heart conditions. This research focused on building a predictive model to identify cardiovascular diseases (CVD) using ECG data. A dataset comprising 2,840 12-lead ECG recordings was gathered from medical facilities in Gazipur, Bangladesh, over the period from June to August 2024. The …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 51–85 Read article
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Exploring the Effectiveness of IoT in Virtual Doctor Robot Systems
Abstract: The design and development of a Virtual Doctor Robot (VDR) using Internet of Things technology is presented in this study with the goal of facilitating remote medical assistance. In light of the constraints associated with physical presence, especially in underprivileged areas like isolated parts of India during the COVID-19 pandemic, videoconferencing (VDR) is a viable means of bridging the gap between patients and physicians. The VDR makes accurate diagnostic and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 3, 2024 · pp. 13–23 Read article
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Artificial Intelligence-based Chatbot for Disease Prediction
Abstract: Nowadays leading a healthy lifestyle is very important. Sometimes it is even difficult to find proper medical consultation in unsocialized and remote areas. One such solution to these issues is the development of an Artificial Intelligence based Chatbot for Disease Prediction. A Chatbot is a software program that simulates human conversations, through AI’s Natural Language Processing (NLP) capability. A text-to-text chatbot for disease prediction can involve patients into an interactive …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 10, Issue 1, 2023 · pp. 29–36 Read article
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Sustainable Biomedical Polymer Composites Designed through Artificial Intelligence Approaches
Abstract: The development of sustainable biomedical polymer composites has become one solution that can be used to combat increasing environmental issues that have been presented by traditional medical materials without compromising functional performance. Implementation of the artificial intelligence (AI) in material design presents a paradigm shift of data-driven development, which improves the efficiency, accuracy, and scalability of composite development. The given work can serve as a universal guideline in developing biodegradable …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Prediction of Human Heart Disease
Abstract: AbstractData mining techniques have been widely used in clinical decision support systems for prediction and diagnosis of various diseases with good accuracy. These techniques have been very effective in designing clinical support systems because of their ability to discover hidden patterns and relationships in medical data. One of the most important applications of such systems is in diagnosis of heart diseases because it is one of the leading causes of …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 27–31 Read article
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Advanced Computational Models for Predicting Molecular Interactions
Abstract: Understanding molecular interactions is essential for a number of disciplines, including biochemistry, materials science, and medication development. Traditional experimental methods, while accurate, are often time-consuming and expensive. Advanced computational models have emerged as powerful tools to predict molecular interactions efficiently. In order to predict the behavior and interactions of molecules at the atomic and subatomic levels, this paper reviews the most recent developments in computational techniques, such as machine learning …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 1, 2024 · pp. 8–13 Read article
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A Voice Based Framework in Medical Emergency and Essential Services Using NLP (In Special Reference to People with Writing Disability)
Abstract: Natural Language Processing (NLP) has become increasingly popular in recent years as a means of organising and structuring knowledge for tasks such as translation, summarization, named entity recognition, relationship extraction, and audio recognition. The processing efficiency of NLP based systems has increased significantly with the introduction of deep learning algorithms. The COVID-19 pandemic has posed a challenge to medical research, information technology operations, corporate procedures, and the global economy. Several …
Published in Recent Trends in Programming languages · Vol. 9, Issue 2, 2022 · pp. 1–7 Read article
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Disease Prediction System Using Data Mining
Abstract: The project's main goal is to develop a system that allows users to get personalized advice on their health problems using data mining techniques. In today's hectic world, most individuals overlook this asset, which could be due to a lack of time or the intricacy of the massive data available on the internet. Our goal is to evaluate data processing techniques in clinical and health care settings in order to …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 9, Issue 1, 2022 · pp. 9–13 Read article
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Digital Therapeutics for Management of Chronic Diseases
Abstract: Digital therapeutics (DTx) mark a major advancement in modern medicine, using advanced software technologies to deliver clinically validated treatments for various physical and mental health conditions. Unlike general wellness apps that focus on fitness or lifestyle tracking, DTx are evidence-based medical interventions developed through rigorous clinical research to ensure safety, efficacy, and measurable outcomes. Delivered via digital platforms such as smartphones, tablets, or specialized medical devices, DTx aim to prevent, …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 2, 2026 Read article
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Smart Patient Monitoring and Motion Tracking System
Abstract: The integration of smart technologies in healthcare has revolutionized patient monitoring and diagnostics. This paper presents a Smart Patient Monitoring and Motion Tracking System designed for hospitals, leveraging EEG (Electroencephalogram) signals to track patient movements and monitor neurological health. The proposed system combines motion tracking with real time EEG signal analysis to enhance patient safety, especially for individuals prone to seizures, neurological disorders, or other mobility-related risks. The system employs …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 9–23 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article