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211 articles for “medical machine learning”
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Empowering Healthcare Through IoMT: Unveiling the Architecture, Protocols, and Applications
Abstract: The "Internet of Things" (IoT) is the infrastructure of web-connected devices that automatically gather and transport data through a remote network. Due to the rapid growth of IoT-based gadgets and their expansion towards making medical care facilities financially smart, proactive, and customizable, the "Internet of Medical Things (IoMT)" is presumed proactive in all areas of healthcare. Using cutting-edge technology, the IoMT-based healthcare system offers rapid and reliable treatment, increased communication, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 10, Issue 2, 2023 · pp. 10–23 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Orthostride: An Internet of Medical Things-Enabled Smart Rehabilitation Footwear System for Real-Time Monitor
Abstract: The orthopedic rehabilitation goal of controlled weight bearing, a stable gait progression, and early recognition of hazardous situations for safe mobility is traditionally met through time, scheduled in-clinic observation and clinician induction, and patient report. In this work, Orthostride, a smart rehabilitation footwear prototype intended to augment postoperative and injury-related lower extremity restoration through continuous sensing, embedded decision logic, local feedback, and remote telemetry, is proposed. This system incorporates force …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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Artificial Intelligence -Driven in Clinical Pharmacy Practice: Transforming Medication Management and Patient-Centred Care
Abstract: Artificial intelligence (AI) is transforming clinical pharmacy practice by enhancing the safety, accuracy, and efficiency of medication management while supporting evidence-based clinical decision-making. Recent advances in machine learning, deep learning, natural language processing, and predictive analytics have enabled the integration of AI into various aspects of pharmacy practice, including drug discovery, pharmacovigilance, clinical decision support, personalized medicine, medication adherence, and patient counselling. The objective of this review is to provide …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 3, 2026 Read article
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Role of Medical and Assistive Robotics for Next Generation Healthcare
Abstract: The integration of medical and assistive robotics into healthcare systems is revolutionizing the landscape of patient care and quality of life, heralding the dawn of Next Generation Healthcare. This study explores the multifaceted role of these innovative technologies in reshaping the healthcare paradigm, from diagnosis and treatment to rehabilitation and daily living assistance. Medical robotics, a rapidly evolving field, has led to the development of precision surgical tools, telemedicine platforms, …
Published in Journal of Advancements in Robotics · Vol. 10, Issue 2, 2023 · pp. 1–9 Read article
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AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article
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Enhancing Cancer Diagnosis: AI/ML Algorithms and Nanotechnology-Based Biosensors for Colorectal Cancer Screening
Abstract: Colorectal cancer (CRC) is one of the most common and deadly cancers worldwide, and enhancing patient outcomes requires early identification. This study explores the potential of nanotechnology- enhanced biosensors and artificial intelligence/machine learning (AI/ML) algorithms to revolutionize colorectal cancer screening and diagnosis. Nanotechnology offers unique opportunities for the development of highly sensitive and specific biosensors capable of detecting cancer biomarkers at an early stage. By incorporating nanomaterials with exceptional optical, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 1, 2024 · pp. 16–28 Read article
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AI-Enhanced Interpretation of Cardiac Troponins: Toward Predictive Precision in Myocardial Injury
Abstract: Background: Cardiac troponins (cTn) represent the gold standard biomarkers for myocardial injury detection, yet their interpretation remains challenging due to various confounding factors and clinical contexts. Artificial intelligence (AI) technologies provide remarkable possibilities to improve the interpretation of troponin levels by utilizing pattern recognition, predictive modeling, and clinical decision-making support. Objective: This review examines the current state and future potential of AI-enhanced cardiac troponin interpretation, focusing on machine learning applications, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Smart Wearable Health Pendant Using IoT and Machine Learning for Heart Rate Monitoring and Detecting Falls
Abstract: Cardiovascular illnesses and accidental falls frequently occur among individuals and at-risk populations. This is the reason we genuinely require a device that can monitor their well-being continuously. We are referring to a health pendant designed for seniors and groups at risk can wear. This health pendant leverages Internet of Things technology and machine learning to monitor heart rate and identify falls. Our health pendant system incorporates an ESP32 microcontroller, a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Decode Human Immune System for Blood Disease Detection using Machine Learning Algorithms
Abstract: Quick and accurate medical diagnosis are crucial for the successful treatment of diseases. Using machine learning algorithm and based on laboratory blood test result, we have built a model to predict hematology diseases. It is a predictive model which uses various symptoms causing the disease and a few blood parameters to detect the disease. Blood analysis is an essential indicator for many diseases. It contains several parameters which are sign …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 2, 2020 · pp. 9–14 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Literature Review Discussion of Machine Learning Algorithms for Predicting Chronic
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 Read article
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A Systematic Review for Heart Disease Prediction Using AIML Algorithms
Abstract: Cardiovascular diseases (CVDs), commonly known as heart diseases, have consistently held the position of being the primary global cause of mortality for many years. They are also the most serious illness in India and the rest of the world. So, a method that is reliable, accurate, and easy to use is needed to find these diseases early and start the right treatment. Using a variety of medical datasets, machine learning …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 53–61 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Smart Polymer Composite Scaffolds for Tissue Engineering with Integrated Machine Learning Feedback
Abstract: Another potential solution to improving the results of tissue engineering is smart polymer composite scaffolds, which are capable of dynamic adaptation to changing biological factors, but typical scaffolds cannot change dynamically. This paper suggests a comprehensive system to integrate biodegradable polymer composite scaffolds with sensing and machine learning-based feedback to allow the real-time monitoring and active regulation of tissue regeneration events. The system uses biocompatible materials of PLA/PCL composite of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article