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1068 articles for “diseases”
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 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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Identification of Promising Lead Compounds from Capsicum annuum Targeting BACE-1 for Alzheimer’s Disease Therapy: A Molecular Docking Study
Abstract: Background: Alzheimer's disease (AD) is a neurodegenerative disorder affecting millions of people worldwide. Beta-secretase 1 (BACE-1) is an important therapeutic target for AD treatment. Capsicum annuum (CA) is a commonly consumed plant with potential neuroprotective properties. In this study, we aimed to identify potential lead compounds from CA that can target BACE-1 for AD therapy using molecular docking. Methods: A library of 15 compounds from CA was obtained from PubChem, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 1, 2023 · pp. 40–49 Read article
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Transformative Breakthroughs: Revolutionizing Potato Disease Detection Through Machine Learning
Abstract: Advancements in agricultural technology and the integration of artificial intelligence for diagnosing plant and leaf diseases are crucial for sustainable agricultural development. Conditions like early blight and late blight exert a notable influence on both the quality and quantity of potato harvests. Identifying these leaf diseases manually demands significant labor and a considerable level of expertise. Therefore, efficient, and automated methods for disease detection are essential to improve potato production. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 54–62 Read article
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A Perspective Review on Role of Environmental Pollutants in Developing Neurodegenerative Diseases
Abstract: As human society progresses towards industrialization, an excess number of environmental pollutants are released to our ecosystem, which significantly contribute in causing various health issues primarily associated with neurodegenerative diseases such as cognitive disorder, dementia, anxiety, Alzheimer, Parkinson etc. Because of their high global occurrence, these diseases have attracted attention in recent decades, however, the etiology of these diseases remains unclear. Pollutants are discharged into the environment by natural events …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 2, 2024 · pp. 1–18 Read article
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Association Rule Mining for Predicting Heart Disease: Challenges and Opportunities
Abstract: The exponential growth of digital healthcare data has spurred innovative applications of data mining techniques in medical research and practice. Among these, association rule mining stands out for its ability to uncover meaningful correlations within diverse datasets, such as electronic health records, imaging data, and genetic information. This paper reviews the application of association rule mining in predicting heart diseases, emphasizing its potential to enhance early detection, risk stratification, and …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 29–34 Read article
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Development of Polymer-based Mulch Films for Disease Suppression
Abstract: Gerbera jamesonii [Gerbera daisy) is a popular flowering plant susceptible to various microbial diseases. This paper explores disease control strategies for gerberas, focusing on the potential of novel polymer-based mulch films. Conventional mulching practices offer benefits in gerbera cultivation, including weed suppression that helps control pathogens. However, limitations associated with traditional mulch materials necessitate exploring alternative solutions. This study investigates the development of biodegradable polymer-based mulch films specifically designed for …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 856–863 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Plant-Derived Vaccines: A Sustainable Approach to Disease Control for Global Health
Abstract: Plant-based vaccines present a novel and environmentally responsible approach to vaccination, with significant potential for improving both human and animal health. These vaccines are safer and less expensive than traditional vaccine manufacturing methods because they use genetically modified plants to create antigens that elicit an immune response. Plant-based systems offer a potential remedy for traditional vaccines' high production costs and environmental impact, which are growing problems. Plant-derived vaccines have shown …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 1, 2025 · pp. 17–20 Read article
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A Comprehensive Review on Pharmacological and Therapeutic Uses of Azadirachta Indica in the Treatment of Various Diseases
Abstract: In ancient medicine, the majority of illnesses were treated with plants and phyto-compounds. The most beneficial traditional medicinal plant is Azadirachta indica (Neem). In Ayurveda, it has several therapeutic effects. One of the most adaptable medicinal herbs, it exhibits a broad range of biological action. It possesses medicinal qualities, including anti-microbial, and high efficacy and safety agents. The biologically active components of this plant have a wide range of uses. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 14–25 Read article
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Molecular Docking of Arjuna Tree Phytocompounds for Ischemic Heart Disease
Abstract: Heart disease is a serious condition that can be caused by several lifestyle changes and sometimes genetic problems. The primary protein component of apolipoprotein is the LDL receptor, which indicates that a reduction in LDL levels can reduce the risk of ischemic heart disease. Apolipoprotein levels are associated with increased levels of ischemic heart disease. Using ADMET analysis, drug likelihood prediction, and molecular docking, this work attempted to find natural …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 42–52 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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An Overview of Artificially Generated Neural Networks Inside the Brain’s Structure in an Alzheimer’s Disease Patient
Abstract: Alzheimer’s disease produces significant neuronal loss, while the precise mechanisms and timing are yet unknown. Other types of cell death, such necroptosis, parthanatosis, ferroptosis, and cuproptosis, need further investigation. Based on brain images of people with mild cognitive impairment, this study assesses artificial neural networks (ANNs) used to diagnose and predict Alzheimer’s disease (AD). This research was conducted considering growing recognition among researchers and medical professionals regarding the importance of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 2, 2025 Read article
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Review of Atorvastatin As A Potent Drug For Cardio-Vascular Disease(CVD)
Abstract: Cardiovascular disease (CVD), particularly atherosclerosis, remains the leading cause of death worldwide, significantly burdening public health, especially in Western societies. Metabolic syndrome and arrhythmic complications further exacerbate cardiovascular morbidity and mortality. Among restorative specialists, statins particularly atorvastatin have gotten to central in both the essential and auxiliary anticipation of coronary heart infection (CHD) due to their strong lipid-lowering properties and additional pleiotropic impacts. Atorvastatin, a selective HMG-CoA reductase inhibitor, not …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 8–18 Read article
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Advances in Polymer Chemistry for Coronary Artery Disease
Abstract: Coronary artery disease (CAD) remains the leading cause of morbidity and mortality worldwide, driving ongoing innovation in therapeutic materials and device design. Polymer chemistry has emerged as a cornerstone in the development of advanced cardiovascular interventions, offering versatile platforms to improve the safety, efficacy, and functionality of implantable devices. This review explores recent advances in the synthesis and application of biodegradable and biostable polymers, focusing on their roles in drug-eluting …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 710–716 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Efficacy of New Fungicides in Controlling Powdery Mildew of Sweet Gourd
Abstract: This experiment was conducted at the Plant Pathology Division, Regional Agricultural Research Station (RARS), Jamalpur, Bangladesh during 2025 of Rabi & Kharif-1 seasons to find out the effectiveness of new fungicides against Powdery mildew disease of sweet gourd. Twenty (20) new fungicides viz. Acrozet 50 WP, Qingdao GBW, Hea 10 FC, Top star 32.5 SC, Nila 80 WP, Soazeb 72 WP, Safezeb 80 WP, Canvas 32.5 SC, Pyzim 50 WP, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 134–142 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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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article