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297 articles for “Disease Identification”
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Identification and Categorization of Brain Tumors
Abstract: Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Strategic and well-thought-out treatment planning significantly contributes to improving a patient's overall quality of life. Many different imaging techniques, such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and also ultrasound are used to evaluate tumors in different parts of the body, with a focus on using MRI images for brain tumors. It is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 2, 2023 · pp. 32–37 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Dengue in India : Insights in the Indian Context
Abstract: The mitigation of infectious diseases in India, notably Dengue, assumes pivotal importance due to their significant repercussions on human and animal health, thereby imposing a considerable burden on the healthcare infrastructure. This review underscores the ongoing initiatives in infectious disease management, endorsing the implementation of a comprehensive healthcare strategy. Emphasis is placed on the augmentation of reporting mechanisms through the integration of IgM detection kits, advocating for heightened investments in …
Published in Recent Trends in Infectious Diseases · Vol. 1, Issue 2, 2024 · pp. 10–13 Read article
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An Expected Cardiovascular Disease Detection Using Deep Learning Techniques
Abstract: Many avoidable deaths globally are caused by CVD, often due to individuals remaining unaware of their risk factors until severe symptoms, such as heart attacks or strokes, appear. This study utilizes retinal images as the dataset to explore the potential of retinal imaging as a non-invasive diagnostic tool for early detection of cardiovascular diseases (CVD). The delay in diagnosis and treatment highlights the need for sophisticated diagnostic instruments that can …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 Read article
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Marine-Derived Pharmaceuticals: Unlocking the Ocean's Potential for Human Health
Abstract: The ocean, covering 70% of the Earth’s surface, is a rich source of unique bioactive compounds with potential therapeutic applications. This review aims to highlight the significance of marine-derived pharmaceuticals in human health, focusing on clinically approved and commercially available medications. The review covers various marine-derived compounds, their structural features, modes of action, and applications in treating diseases, such as cancer, diabetes, and neurodegenerative disorders. The review identifies several marine-derived …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Computational Identification of Antigenic Proteins and Epitopes in Hantavirus sp. for Drug Repurposing
Abstract: Hantavirus is an emerging virus that spreads from animals to humans and can cause serious illnesses like hantavirus pulmonary syndrome (HPS) and hemorrhagic fever with renal syndrome (HFRS). there are no FDA-approved treatments available for these diseases. This study explores in-silico drug repurposing as a strategy to identify potential therapeutic candidates. The physicochemical, secondary structure, antigenicity, and post-translational modification analysis of hantavirus proteins – specifically the glycoprotein precursor, N protein, …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 1, 2025 · pp. 20–26 Read article
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DentiDetect: Dental Diagnosis Powered by Deep Learning
Abstract: Dental X-rays play a crucial role in modern dentistry, enabling dentists to detect cavities, bone loss, and other hidden dental issues that are not easily visible during a routine examination. X-rays offer a clear picture of teeth, bones, and nearby tissues, enabling early identification of issues. This helps create more efficient treatment strategies and improves patient outcomes. Three commonly used types of X-rays include bitewing, periapical, and panoramic. Bitewing X-rays …
Published in Research and Reviews: A Journal of Dentistry · Vol. 15, Issue 3, 2024 · pp. 21–26 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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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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Targeting PTPN22 in Arthritis: Molecular Docking and Pharmacokinetic Evaluation of Artemisia vestita Compounds
Abstract: Rheumatoid arthritis (RA) is a long-term autoimmune condition characterized by inflammation of the synovial membrane, commonly resulting in swelling, pain, stiffness, and overall fatigue. Protein tyrosine phosphatase non-receptor type 22 (PTPN22) has been identified as a risk factor linked to various autoimmune diseases, including RA. In the PTPN22 gene, two missense Single nucleotide polymorphisms (SNPs) are associated with autoimmune conditions. The R620W (C1858T, rs247660) variant in exon 14 has been …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 1, 2025 · pp. 20–31 Read article
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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 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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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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Comprehensive Perspective on Coronary Heart Disease: A Review
Abstract: The study explores intricate links between infections, inflammation, and coronary heart disease (CHD), emphasizing their multifaceted contributions to cardiovascular complications. It identifies infections as key players in atherosclerosis, a pivotal element in CHD development, with high antibody levels to specific pathogens as potential risk factors. The article highlights the role of the immune response and elevated C reactive protein (CRP) levels in amplifying infection-related CHD risks and recognizes smoking as …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 1, 2024 · pp. 26–40 Read article
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Comparative Proteomics: From Cell Lines to Clinical Samples
Abstract: Comparative proteomics is a powerful tool for understanding the molecular differences between various biological samples. It entails identifying and measuring proteins in complex biological samples to assess their abundance, modifications, and interactions under various conditions. This approach plays a crucial role in advancing biomedical research, especially in disease understanding, biomarker discovery, and therapeutic development. While cell lines are widely used for proteomic studies due to their controlled environments and reproducibility, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 30–34 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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Nanotechnology-Enhanced Wearable Biosensors for Liver Disease Detection: Integration with AI for Predictive Analytics
Abstract: The worldwide health burden of liver diseases is substantial, and effective treatment and management depend heavily on early detection. This study investigates the integration of nanotechnology-enhanced wearable biosensors with artificial intelligence (AI) techniques for predictive analytics in liver disease detection. The construction of extremely selective and sensitive biosensors that can identify a variety of biomarkers linked to liver illnesses has been made possible via nanotechnology. These nanotechnology-based biosensors can be …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 14, Issue 1, 2024 · pp. 22–36 Read article
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Computational Exploration of Bhrijraj-derived Phytochemicals as Potential Anti-inflammatory Agents: A Molecular Docking Study with Cyclooxygenase-II Complex
Abstract: The molecular docking analysis was meticulously conducted using state-of-the-art computational tools, notably Chimera and Python. These tools were employed to unravel the complex interactions between the identified phytochemicals from Bhrijraj and the target protein, COX-II. The 3D structures of the phytochemicals were prepared with precision using ChemSketch, ensuring accuracy in the subsequent molecular docking simulations. This rigorous approach enhances the reliability and validity of the findings. This research aims to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 1, 2024 · pp. 31–37 Read article