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194 articles for “Healthcare Data Modeling”
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Artificial Intelligence in Diagnostics: Advancements, Challenges, and Future Prospects
Abstract: AI is changing (and will change) healthcare as we know it, and diagnostics might be the specialty that feels the most discomfort. Artificial intelligence-based analytical systems are facilitating the detection, diagnosis, and treatment of a variety of diseases, with better accuracy, speed, and results. Now, this abstract investigates the role of AI in diagnostics, scouring its elements, landmark techniques, transformative impact and future overview. This article explains AI and discusses …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 8–17 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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Natural Language Processing in Everyday Applications: From Classrooms to Clinics
Abstract: Natural Language Processing (NLP) is transforming everyday sectors like healthcare and education by creating new opportunities for efficiency, accessibility, and early intervention. This paper investigates the function of natural language processing (NLP) in computer education. Tools like automated grading systems, intelligent tutoring assistants, and multilingual translation platforms are revolutionizing traditional teaching methods. Despite its benefits, adoption is still being slowed down by problems like data privacy, integration with education, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 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
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Wastewater Management in Smart Cities Using PLC and SCADA
Abstract: Smart cities are the best examples to improve the standard of living of people in any country. Cities are made smart by integrating smart systems, that is, water supply system, electricity control system, smart communication technology etc. In this study, a model has been developed for controlling the water supply system for a smart city using PLC (Programmable Logic controller) and SCADA (Supervisory Control and Data Acquisition). A case study …
Published in Current Trends in Signal Processing · Vol. 10, Issue 3, 2020 · pp. 32–41 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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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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Symmetry Principles in Digital Twin Systems: Modeling, Integration, and Applications
Abstract: This systematic review comprehensively examines the burgeoning field of Digital Twin (DT) technology, analyzing its current state, diverse applications, and future trajectory. Through a rigorous methodology involving a systematic search of academic databases and relevant industry literature, this review synthesizes findings across a spectrum of disciplines. We identify the core components and underlying principles of DTs, distinguishing them from traditional simulation models by their dynamic, realtime data integration and bi-directional …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 06–24 Read article
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Role of Blockchain Technology in Health Record Management
Abstract: Maintaining thorough medical records is essential to raising a healthy population in the fast-paced world of global development. Intimidating data breaches have been the consequence of the traditional centralized strategy to maintaining health records, yet it has proven vulnerable. The 2017 Ponemon Cost of Data Breach Study estimated that each compromised healthcare record could incur a significant cost of approximately $380. Regrettably, the 2016 Breach Barometer Report revealed that case …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 1, 2024 · pp. 29–35 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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Advancing Healthcare Systems: A Machine Learning Approach to Multi-Disease Prediction
Abstract: The integration of machine learning algorithms in healthcare has revolutionized the way we approach disease prediction and diagnosis. An attempt to employ machine learning techniques to forecast numerous diseases is presented in this study. A diverse dataset containing patient records, medical history, and relevant features for various diseases was used to develop predictive models. Feature selection and normalization were among the preprocessing methods used to clean and prepare the data. …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 1, 2025 · pp. 1–6 Read article
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Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine
Abstract: Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 52–59 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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Collaborative Care for Diabetic Retinopathy: Integrating Artificial Intelligence and Clinical Pharmacy Services - A Comprehensive Review
Abstract: Background: Diabetic retinopathy (DR) remains the leading cause of blindness among working-age adults globally, affecting approximately 103 million people worldwide. The integration of artificial intelligence (AI) technologies with clinical pharmacy services presents unprecedented opportunities to enhance screening, diagnosis, and management of DR through collaborative care models. Objective: This comprehensive review examines the current landscape of collaborative care approaches for diabetic retinopathy management, focusing on the integration of AI-powered diagnostic tools …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 118–128 Read article
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A Five-Layer Architectural Framework for Sustainable and Scalable AI Systems
Abstract: Artificial Intelligence (AI) is not only about algorithms. AI works like a full “stack” of layers, from electricity to real-world user applications. In this paper, we explain a simple and student-friendly Five- Layer Architecture of AI: (1) Energy, (2) Chips, (3) Infrastructure, (4) Models, and (5) Applications. Each layer supports the next layer, like a cake with multiple layers. If any layer is weak, AI systems become slow, costly, or …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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A Comprehensive Study of Natural Language Processing Systems Using Modern Programming Languages: Techniques, Architectures, Experimental Evaluation and Applications
Abstract: Natural language processing is a key field of study within artificial intelligence that focuses on enabling machines to understand and work with human language. This is because there is much digital text data everywhere. Natural Language Processing is what this study is about. It looks at new ways of doing Natural Language Processing. The old ways are like machine learning, and the new ways are like learning. This study compares …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 12–23 Read article
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A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article