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361 articles for “AI in Healthcare”
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Artificial Intelligence based Point of Care Device in Advanced Medical Diagnostic Techniques
Abstract: Application of Point-of-Care Testing (POCT) at medical sites provides instant diagnostic results that help doctors make quick decisions for patient care. The traditional point-of-care testing equipment faces restrictions because they test single parameters and experience calibration problems in addition to inefficient data management systems. POCT technology benefits from the integration of Artificial Intelligence (AI) which creates a novel system to solve current operational limitations. The presented study introduces an intelligent …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
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Transforming Rare Disease Diagnosis with AI
Abstract: Artificial intelligence is changing healthcare fast. It is making diagnoses accurate, helping doctors get better results, and streamlining how care works. This paper looks at how AI shows up in healthcare right now – where it is already making a difference, what is working, and what is still tricky. The focus is on machine learning, natural language processing, and computer vision. Particular attention is given to using AI in diagnosing …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 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
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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A MediStream Application: Integrated Application for Patient Data and Medical Oversight
Abstract: Maratha Vidya Prasarak Samaj (MVPS) has periodic health check-ups for the students and teachers, however, traditional paper-based records systems are prone to inefficiencies, data loss and administrative overhead. To resolve this issue, a Student Health Record System that is digital in nature is proposed which ensures up-to-the-minute security and management of health information. The system is built with JavaScript, XML, Fire base and offers role-based access for administrators, doctors, interns, …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 1–6 Read article
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The Future of Healthcare: Role of Artificial Intelligence in Revolutionizing Nursing
Abstract: Artificial intelligence (AI) is rapidly transforming the healthcare industry, and nursing professionals stand to benefit significantly from its integration. This article explores the role of AI in revolutionizing nursing, highlighting its applications, benefits, challenges, and ethical considerations. Drawing on examples from countries actively integrating AI into nursing services such as the United States, the United Kingdom, China, and Japan, the article discusses how AI supports nursing tasks, enhances patient care, …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 1, 2024 · pp. 1–5 Read article
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Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
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A Comprehensive Review of Machine Learning and Explainable AI Techniques for Disease Prediction Systems
Abstract: Large amounts of diverse medical data have been produced because of the quick development of digital healthcare systems, offering substantial chances to use machine learning methods for clinical decision support and illness prediction. By identifying intricate patterns in clinical data, machine learning-based models have shown great promise in early disease detection, risk assessment, and personalised healthcare. However, issues with transparency, interpretability, and reliability have been brought up by the growing …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 20–28 Read article
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Role of Artificial Intelligence in Health Care Decision Making: Balancing Innovation and Caution
Abstract: Healthcare is undergoing a transformation powered by artificial intelligence, which improves monitoring, diagnosis, and treatment capabilities. Among Artificial Intelligence (AI's) shortcomings is the dearth of an emotional relationship between individuals and medical personnel. Robotic surgery procedures pose the possibility of malfunctioning machinery and mistaken assumptions. So, the present systematic review focused on exploring the boon and bane of the role of AI in predicting various abnormalities in advance to improve …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 24–35 Read article
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The Future of Robotics: A Review of AI-Enabled Robotics Research, Development, and Applications
Abstract: Robotics powered by artificial intelligence (AI) is transforming contemporary industries by empowering machines to learn, adapt, and operate on their own in intricate, changing contexts. The breadth and capabilities of automation have been greatly expanded by the convergence of AI technologies with robots, including machine learning, deep learning, computer vision, and natural language processing (NLP). With an emphasis on technological advancements, application areas, and research advances, this study examines current …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 33–38 Read article
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Emotionally Intelligent AI: The Future of Mental Health Care and Emotional Well-being
Abstract: With the potential to improve emotional well-being through sophisticated AI systems, emotionally intelligent AI (EI-AI) represents a revolutionary frontier in mental health treatment. EI-AI can recognize, understand, and react to human emotions in real- time by utilizing recent advancements in machine learning, natural language processing, and emotion detection. These features are being used more and more in mental health settings, where chatbots and other AI-driven interventions help with emotional regulation, …
Published in Recent Trends in Social Studies · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Report Pulse: Using Machine Learning
Abstract: This study presents the development of a novel medical report analyzer, specifically designed to streamline the interpretation of complex health data. The Report Pulse project represents a significant advancement in healthcare innovation, aiming to facilitate deeper insights into medical reports and foster personalized health management strategies. At its core, the Report Pulse project introduces a sophisticated blood report analyzer, which transcends conventional data analysis by providing actionable insights tailored to …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 28–33 Read article
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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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Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 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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A Comprehensive Review of DiagnoTech: Your Healthcare Companion
Abstract: The review paper “A comprehensive review of DiagnoTech: Your Healthcare Companion” brings forth a transformative solution in the advancements of healthcare technology which aims to be an all-in-one Healthcare Companion. It explores the four key elements of DiagnoTech: Lab Tests, Body Mass Index (BMI) Calculation, Yoga and Diet Recommendations, and disease prediction. It brings to light each of these features’ functionalities, integration, and their collective impact on the healthcare industry. …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 2, 2024 · pp. 24–32 Read article
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 Read article