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193 articles for “disease prediction”
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 Read article
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Explainable Artificial Intelligence in Personalized Medicine: Emerging Clinical Perspectives
Abstract: The convergence of artificial intelligence (AI) and precision medicine has transformed contemporary healthcare by enabling data-driven clinical decision-making, individualized therapeutic interventions, and predictive diagnostics. However, despite remarkable advances in machine learning (ML) and deep learning (DL), the widespread adoption of AI in healthcare remains constrained by the “black-box” nature of many computational systems. Clinicians, regulatory agencies, and patients increasingly demand transparency, interpretability, and trustworthiness in AI-guided medical recommendations. Explainable Artificial …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 13–29 Read article
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Aquaculture and Computers—Innovations and Applications
Abstract: Aquaculture, the cultivation of aquatic organisms for commercial purposes, has grown significantly over the past few decades due to the increasing global demand for seafood. The integration of computer technologies into aquaculture has revolutionized the industry, enabling more efficient management of resources, improved production processes, and enhanced sustainability. Computers and digital systems facilitate real-time monitoring of water quality, fish health, and feeding systems, while data analytics and artificial intelligence (AI) …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 70–85 Read article
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Long Non-Coding RNAs: Key Regulators of Gene Expression in Development and Disease
Abstract: Long non-coding RNAs (lncRNAs) are RNA molecules that do not make proteins but are essential for controlling how genes are turned on or off in the body. These molecules help with various biological functions, such as guiding cell growth, shaping development, and influencing the progression of diseases. Recent advancements in genomics and transcriptomics have revealed the vast and complex roles of lncRNAs, with an increasing recognition of their involvement in …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 11–15 Read article
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A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework
Abstract: Emerging Infectious Diseases (EIDs) represent one of the most critical and persistent threats to global health security in the 21st century. Driven primarily by the synergy of unprecedented human encroachment into wild habitats, climate change-induced ecological disruption, accelerated international travel, and antimicrobial resistance, the frequency and severity of zoonotic spillover events are rapidly increasing. Traditional, reactive public health measures—focused on containment after an emergence—have repeatedly proven insufficient, leading to catastrophic …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 1, 2026 · pp. 8–21 Read article
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Multivariant Disease Detection from Different Plant Leaves and Classification
Abstract: Agricultural growth is significant in Indian GDP which is based on yield of crops, quality of the plants and procedure of the plants taken. To maintain good quality of plant, the plant diseases should be identified and then given proper suggestions to farmers for specific fertilizers and pesticides to be used. The use of specific fertilizers or pesticides makes plant more health with good quality so that farmers can get …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 27–35 Read article
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Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
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Kisan Mantra: Enhancing Farmer Productivity, A Web-Based Approach for Efficient Crop Harvesting and Problem Diagnosis
Abstract: India's agricultural sector faces persistent challenges, including limited access to expert guidance, difficulties in managing diverse datasets, unreliable weather forecasting, and a lack of real-time monitoring for farm activities and crop quality. Additionally, farm lenders struggle to obtain accurate insights into farm productivity and risks, hindering their ability to provide tailored financial solutions. The sector also grapples with underemployment among educated professionals, limiting their contributions to agricultural advancement. To tackle …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 71–87 Read article
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Recent Update on Advanced Drug Delivery System
Abstract: Over the past decade, there has been a growing interest in the use of artificial intelligence (AI) technology for analysing and interpreting biological or genetic data, accelerating drug discovery, and identifying selective small-molecule modulators or rare molecules in addition to predicting their behaviour. The use of artificial neural networks (ANNs) for the rapid analysis of massive amounts of data, the development of novel hypotheses and treatment plans, the prediction of …
Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 22–30 Read article
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Harnessing IoT and Sensor Technologies for Smart Agriculture: A Path Towards Viksit Bharat
Abstract: The integration of Internet of Things (IoT) and sensor technologies is redefining the landscape of Indian agriculture, serving as a catalyst for achieving the ambitious vision of Viksit Bharat (Developed India). Indian agriculture faces significant challenges such as resource scarcity, climate variability, and fragmented supply chains, which hinder productivity and sustainability. IoT-based solutions offer innovative approaches to address these critical issues by enabling smart irrigation systems, real-time field monitoring, precision …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 2, 2025 · pp. 38–45 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Epidemiology and transmission of infectious diseases study using Machine learning
Abstract: Infectious diseases remain a formidable global health challenge, characterized by rapid evolution and complex transmission dynamics that often outpace traditional epidemiological surveillance and response mechanisms. This study investigates the transformative potential of machine learning (ML) methodologies to enhance our understanding and prediction of infectious disease epidemiology and transmission. Leveraging diverse datasets—including clinical records, genomic sequences, environmental factors, social mobility data, and real-time digital footprints—we studies and presented various ML models …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Metabolites in Modern Medicine: Decoding the Future of Health and Diseases
Abstract: The end products of many metabolic processes in cells are called metabolites. Each reaction contributes a specific metabolite. Metabolites act as fingerprints of on-going biological processes. Constant changes in cellular composition due to both environmental and internal factors. By analysing the types and presence of metabolites, scientists can effectively reconstruct the inner workings of a cell or organism. In the past, analysing metabolites was a slow and tedious process, often …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 2, 2024 · pp. 1–13 Read article
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Integration of Biomarkers in III and IV CKD Patients for Evaluation of Their Predictive Value for CVD in CKD Patients
Abstract: Background: Chronic kidney disease (CKD) is presently characterized by the presence of proteinuria and/or a diagnosis of renal impairment. The worldwide significance of CKD is underscored by the fact that its prevalence and incidence have doubled over the past three decades. This paper provides an overview of the existing evidence regarding biomarkers in individuals with CVD or CKD, with a particular focus on the emerging biomarkers (i.e., eGFR, sALB, UACR, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–12 Read article
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Clinical metabolomics: Useful insights, perspectives, and challenges.
Abstract: Metabolomics provides a comprehensive snapshot of smallmolecule intermediates and end products of cellular processes and thereby links genotype, environment, and phenotype in human disease . Over the last decade, advances in liquid chromatography–mass spectrometry (LC–MS) and nuclear magnetic resonance (NMR) spectroscopy have enabled high-throughput profiling of thousands of metabolites from microliter volumes of clinical samples . Clinical metabolomics is now emerging as a tool for disease diagnosis, risk prediction, therapeutic …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 1, 2026 · pp. 29–37 Read article
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Intelligent Farming: Integrating AI and IoT for Sustainable Agriculture
Abstract: Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming modern agriculture by enabling data-driven, resource-efficient, and climate-resilient farming practices. This review critically examines recent advances in AI-IoT integration across crop production, irrigation management, pest and disease surveillance, and supply chain optimization through an analysis of published literature and documented case studies. The review indicates that AI-assisted predictive analytics combined with IoT-based real-time sensing significantly improves decision-making in precision …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 Read article