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193 articles for “Disease Prediction”
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Targeting Dystrophin Restoration and Neuroprotection in Duchenne Muscular Dystrophy: Insights from Withania somnifera
Abstract: Duchenne muscular dystrophy is a genetic disorder. This disease affects men more common than women. Main objective of the present study was to identify the naturally active phytocompounds from Withania somnifera (Ashwagandha). Ashwagandha has a great value in the field of Ayurveda and Indian medicine and is used for treating muscular and neurological disorders. Toxicity prediction, molecular docking, statistical information, drug illness prediction, and Absorption, distribution, metabolism, excretion, and toxicity …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 64–84 Read article
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Role of Pharmaceutical Software in Vaccine Development and Manufacturing Process Optimization
Abstract: Vaccine development and manufacturing have become increasingly complex due to the emergence of diverse vaccine platforms, stringent regulatory expectations, and global demand for safe and effective immunization. Across the vaccine lifecycle – from antigen design and preclinical evaluation to large‑scale manufacturing and post‑marketing surveillance – pharmaceutical software now plays a central role in handling data, optimizing processes, and ensuring regulatory compliance. Software tools support in silico antigen and epitope design, …
Published in International Journal of Vaccines · Vol. 3, Issue 1, 2026 · pp. 1–8 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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An Effective Convolutional Neural Network for Identifying Cancer Blood Disorder Cells Using Microscopic Images
Abstract: Blood, bone marrow, and lymphatic systems are all impacted by hematological cancer is known as a cancer blood disorder. Blood malignancies and various blood disorders pose significant health challenges across all age groups. Early disease detection is essential for effective cancer blood disorder treatment and management. If a blood cancer is not identified in time, it may be hazardous. It results in abnormal white blood cell production by the bone …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 29–35 Read article
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Exploring Glucagon-like peptide-1 as a Target Protein for Diabetes Mellitus Treatment: Molecular Docking and Pharmacokinetic Analysis of Phytocompounds from Momordica charantia
Abstract: Objective: This study aimed to use molecular docking techniques to explore the potential of GLP-1 (glucagon-like peptide-1) as a target protein for the treatment of diabetes mellitus, a chronic metabolic disease marked by elevated blood glucose levels. Given its crucial role in maintaining insulin secretion and glucose homeostasis, GLP-1 may serve as a future target for diabetes therapy. Method: The study employed a multi-phase method. Initially, protein extraction was carried …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 1, 2024 · pp. 8–20 Read article
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AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
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Remote Monitoring Sensor Systems and Applications in Health Informatics: Fostering Shell Programming
Abstract: The fascination of sensor systems has been promising for health informatics as their direct initiative for real-time information by observing its accuracy that was required at the time for data collection, monitoring and analysis to improve patient well-being and health system administering. By integrating these systems with wearable devices, biomedical sensors, and other IoT-enabled technologies, patients can experience continuous health tracking, early disease detection, and remote patient monitoring. For example, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Viral Chronicles: The Ever-Evolving Saga of COVID-19
Abstract: Coronaviruses, belonging to the family of RNA viruses, have recently captured global attention owing to their remarkable ability to infect a diverse array of species, ranging from animals to humans. These viral agents, recognized by their characteristic crown-like morphology when observed through electron microscopy, have a historical association with zoonotic diseases. Previous examples include Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) and Middle East Respiratory Syndrome Coronavirus (MERS-CoV). The term "Corona" …
Published in International Journal of Virus Studies · Vol. 1, Issue 1, 2024 · pp. 16–25 Read article
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Machine Learning for Soil Moisture Detection: Introduction, Approaches and Challenges
Abstract: The demand for agricultural is increasing day by day as the population of the world is increasing. So, it becomes necessary for us to increase the production of agricultural products. Traditional ways of agriculture cannot meet such requirements. Nowadays, machine learning based technologies are being used to develop models for agriculture. Machine learning-based applications are very fast and produce high-quality results. It includes recurrent neural networks (RNN), convolution neural networks …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 88–96 Read article
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Machine Learning-Driven Early Prediction and Prevention of Obesity and Overweight
Abstract: Obesity has become a global health concern, with its prevalence reaching alarming levels in recent years. By classifying obesity-level, healthcare professionals can assess an individual's risk and develop appropriate treatment and prevention strategies. Healthcare professionals can customize interventions and create personalized treatment plans based on individual needs. This paper delivers a system provides an overview of obesity, highlighting the importance of accurate and standardized categorization for effective management and treatment …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 31–40 Read article
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Antimicrobial Peptides in Fiddler Crabs: Structural Analysis and Potential Applications
Abstract: Crustaceans represent the largest and most ecologically and economically significant group of marine and aquatic arthropods. Their biomass and critical role in ecosystems highlight their importance. Among crustaceans, decapods are frequently used as model organisms in studies of immune responses due to their significant commercial value and the need to mitigate disease outbreaks in shellfish aquaculture. Antimicrobial host-defense peptides (AMPs) are pivotal in metazoan immunity, especially for invertebrates lacking adaptive …
Published in International Journal of Cheminformatics · Vol. 2, Issue 2, 2024 · pp. 26–32 Read article
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QR Based Plant Care System
Abstract: The QR Based Plant Care System is an innovative digital solution developed to improve plant monitoring, maintenance, and information management through the integration of QR code technology with smart agricultural practices. Traditional plant care methods mainly depend on manual record keeping, handwritten labels, and human observation, which often result in data loss, inconsistency, and inefficient plant management. With the increasing demand for sustainable agriculture and efficient resource utilization, there is …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 32–40 Read article
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Repurposing Approved Immunomodulatory Drugs for Target Proteins in the Pancreas of European eel: A Molecular Docking Approach
Abstract: Leishmaniasis is a disease caused by tiny parasites called Leishmania, which spread to humans through the bite of an infected female sand fly. The disease manifests in three different forms, and the protein calcitonin promotes the disease’s spread. By reducing blood calcium levels, inhibiting osteoclast activity, increasing calcium excretion, and possibly playing a role in neurotransmitter modulation, calcitonin, a hormone released by vertebrates, promotes the progression of pathogenesis and lessens …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 12–19 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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Interaction of Bioactive Component of Aframomum melegueta on Molecular Docking
Abstract: Computational mimicry of the structure of large complexes created by di- and poly-interaction of molecules has been termed molecular docking. The purpose of molecular docking is the prediction of the three-dimensional structures of interest, this is due to that docking only produces plausible candidate structures. The docking was carried out between the bioactive compounds against 5α-reductase, 3β-hydroxy-steroid dehydrogenase, and 17β-hydroxy-steroid dehydrogenase of returned binding energy, BE (kcal/mol) between -5.9 and …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 2, Issue 1, 2024 · pp. 51–60 Read article
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Smart Air Filtration Systems for Cities: A Technological Approach to Reducing Urban Pollution
Abstract: Urban air pollution is considered one of the main ecologically critical issues of the 21st century since it threatens citizens' health through respiratory diseases, pathologies of the cardiovascular system, and even premature death. Regarding an extremely high level of pollution in large cities, it becomes necessary to realize technological solutions which could avoid the negative impact of this phenomenon. Smart air filtration systems have emerged as promising solutions for urban …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 2, Issue 2, 2024 · pp. 27–42 Read article