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211 articles for “medical machine learning”
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Artificial Intelligence: Revolutionizing Indian Healthcare
Abstract: Artificial Intelligence (AI) has achieved a tipping point. The blend of the innovation, information and ability that makes astute frameworks conceivable has achieved minimum amount, driving uncommon development in AI venture. Over the world, G20 nations have been developing their AI capacities. Individuals and insightful improvements cooperating inside and outside organizational boundaries to produce improved results for clients and society are at the heart of AI’s power. AI has also …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 1, 2022 · pp. 17–24 Read article
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Illuminating the Frontier of Drug Discovery: Unleashing the Power of Bioinformatics for Unprecedented Breakthroughs
Abstract: It takes a long time and a lot of effort to discover and develop new drugs, which necessitates extensive study and testing. With the help of computational techniques and data analysis, bioinformatics has grown to be a potent tool for drug discovery in recent years, allowing researchers to find new drugs faster. In this review, we examine the role of bioinformatics in drug discovery, including the use of ligand- and …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 2, 2023 · pp. 1–10 Read article
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Comparative Analysis of Heart Disease Prediction System
Abstract: In the present world, where heart illnesses are on the rise, it is crucial to forecast these diseases. Performing the task on heart disease is a bit difficult and it must be finished precisely and successfully. Heart disease identification relies heavily on Machine Learning (ML) and data mining approaches. The primary focus of the review paper is that patients are easily prone to cardiac diseases depending on medical traits. Using …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 1–6 Read article
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A Study on Feature Subset Selection in Feature Streams of Dynamic Data
Abstract: As the use of real-time data with high dimensions continues to expand across various domains, selecting important features from the dataset is a key step to improve the predictive accuracy and time taken to build a machine learning model. In datasets where not all features are available at the same time and we are unaware of the total number of features, and features arrive at different time stamps, for example, …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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Artificial Intelligence in Medical Fields
Abstract: Artificial intelligence (AI) is a branch of computer science capable of analyzing complex medical data. This can be used in diagnosis, treatment and predicting outcome in many clinical scenarios. Medicine and internet searches were carried out using the keywords ‘artificial intelligence’ and ‘neural networks’. An overview of different AI techniques is presented in this paper along with the review of importance in clinical applications. The proficiency of AI techniques has …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 8, Issue 1, 2019 · pp. 1–3 Read article
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Wireless Biosensing Polymer Composites for Smart Healthcare Devices
Abstract: The wireless biosensing polymer composites have been found as one of the possible solutions in developing flexible, real-time and intelligent healthcare monitoring systems. Biomimic polymer matrices coupled with conductive nanomaterials can be used to design an understanding of physiological signals (strain, pressure, and temperature) that are highly sensitive and adaptable sensors. The attachment of these sensors to wireless communication systems, such as the Bluetooth Low Energy and Wi-Fi, eases the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 14, 2026 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 Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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AI: Revolutionizing Pharmacy Practice and Enhancing Patient Care and Safety
Abstract: The use of artificial intelligence (AI) in pharmacy is transforming medication management, improving patient care, and boosting safety. By leveraging cutting-edge technologies, such as machine learning, natural language processing, and predictive analytics, AI enables pharmacists to develop personalized treatment plans and anticipate possible adverse drug reactions. AI-driven systems enhance operational efficiency by streamlining inventory management, prescription processing, and administrative duties, allowing pharmacists to devote more time to patient care. Additionally, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 13–20 Read article
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Advances in Medical Robotics: Surgical Automation and Rehabilitation Systems
Abstract: Medical robotics has emerged as a groundbreaking technology, transforming modern healthcare through advancements in surgical automation and rehabilitation systems. Robotic-assisted procedures machine learning (ML), and artificial intelligence (AI) have all been used to improve patient recovery consequences, reduce invasiveness, and increase surgical precision. These developments have redefined traditional medical techniques by opening the door for more effective, precise, and tailored therapies. By improved dexterity, stability, and vision, surgical robots has …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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Automatic Chest X-ray Report Generation Using Machine Learning
Abstract: In this study, a deep neural network is suggested for the automatic creation of precise radiologist reports from chest X-ray pictures. The proposed network responds to the need for medical image captioning by learning to extract key features from the image and creating tag embeddings for each patient's X-ray images. Medical image captioning demands coherence and high accuracy in identifying abnormalities and extracting information. For a finer representation, the network …
Published in Journal of Instrumentation Technology & Innovations · Vol. 13, Issue 1, 2023 · pp. 29–39 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Revolutionizing Veterinary Diagnostics: Nanoparticles and AI Precision
Abstract: The field of veterinary diagnostics is undergoing a transformative revolution propelled by the synergistic integration of nanoparticles and artificial intelligence (AI) precision. Nanoparticles, with their unique physical and chemical properties, present a groundbreaking avenue for enhancing diagnostic sensitivity and specificity in animal healthcare. Engineered to interact with specific biological markers associated with various diseases, nanoparticles offer unprecedented accuracy in early disease detection. Furthermore, their versatility extends to targeted drug delivery, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 25, Issue 3, 2023 · pp. 35–39 Read article
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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The Impact of Artificial Intelligence on the Sales and Marketing of Pharmaceutical Products
Abstract: The rapid development of computing and technology has permeated all branches of science, with artificial intelligence (AI) emerging as a pivotal field in computer science. AI has significantly influenced disciplines ranging from basic engineering to pharmaceuticals. In healthcare and medicinal chemistry, AI applications have become indispensable. Traditional drug discovery approaches are gradually being overtaken by computer-aided drug design. In recent years, artificial intelligence (AI) and machine learning (ML) have become …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 · pp. 10–18 Read article
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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 Read article
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Revolutionizing Blood Cancer Treatment: Emerging Therapies and Future Perspectives
Abstract: Blood cancer inclusive of leukemia, lymphoma and multiple myeloma poses a significant threat in the world today because of its multifactorial process and its non-amenable to standard therapies. Some of such approaches are immunotherapy, gene-editing technology and targeted small molecule inhibitors that have altered the nature of treatments. CAR T cell therapy is a molecular targeted therapy for cancers and several clinical studies have reported a huge success. Also, the …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article