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193 articles for “Disease Prediction”
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Comparative Efficacy and Safety of Safinamide and Rasagiline in the Treatment of Parkinson’s Disease: A Meta-Analysis and Systematic Review
Abstract: Background: Recent studies have suggested Rasagiline and Safinamide monotherapy as potential management options for Parkinson’s disease. Parkinson’s disease, a neurological disorder characterized by tremors and movement difficulties, necessitates treatments aimed at managing clinical symptoms. Levodopa remains the primary effective treatment for Parkinson’s disease symptoms; however, its long-term use often leads to motor complications in many patients. Additional therapeutic drugs, such as dopamine agonists and monoamine oxidase B inhibitors, including Safinamide …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 3, 2024 · pp. 74–91 Read article
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AI-Driven Pharmacogenomics and Precision Medicine: Future of Personalized Therapy
Abstract: Pharmacogenomics and artificial intelligence (AI) are emerging as important drivers of precision medicine, enabling healthcare systems to adopt individualized therapeutic approaches. Pharmacogenomics examines how genetic variations influence drug response, efficacy, metabolism, and toxicity, while AI provides advanced computational tools for analyzing complex genomic and clinical data. This review highlights the integration of AI-driven pharmacogenomics in personalized therapy and its potential to improve treatment outcomes. Machine learning, deep learning, natural language …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 2, 2026 · pp. 1–12 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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DEVELOPMENT OF POLYMERSOMES AS MACROMOLECULAR PLATFORMS FOR NANOMEDICINE
Abstract: The conventional method of drug delivery is plagued with instability, low targeting and low bioavailability. A solution to these shortcomings is the use of polymer Somes, artificial vesicles that are produced through self-assembly of amphiphilic block copolymer, and they are suggested as universal nanoscale carriers. They have stiff, tunable membranes (thickness = 2-50 nm) due to accurate control of polymer chemistry, chain length, and hydrophilic mass fraction (f), which allows …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
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In Silico Analysis and Docking Study of the Active Phyto Compounds of Ginkgo Biloba Against Alzheimer's Amyloid-Beta Protein
Abstract: Objective: Alzheimer's disease, an age-related progressive neurological condition, arises due to the accumulation of amyloid-beta protein within the brain. In this study, an attempt was made to explore the potential of natural compounds derived from Ginkgo, known for their diverse medicinal properties, in the prevention of the disorder by employing molecular docking techniques, conducting drug-likeness prediction assessments, and performing ADME analysis. Methods: Amyloid beta protein was retrieved from the PDB …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 1, Issue 2, 2023 Read article
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Fields of Data: Exploring AI’s Impact on Modern Farming
Abstract: The Food and Agriculture Organization (FAO) of the United Nations projects that by 2050, there will be a further 2 billion people on the planet, but just 4% of that additional land will be used for agriculture. Under such circumstances, the most recent technical developments and solutions to the farming industry’s obstacles can be used to achieve more effective farming methods. The direct implementation of machine intelligence or artificial intelligence …
Published in International Journal of Solid State Innovations & Research · Vol. 1, Issue 2, 2023 · pp. 14–20 Read article
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Computational Biomodeling: Transforming Drug Design with Advanced Simulations
Abstract: Computational biomodeling has emerged as a transformative approach in the field of drug discovery, significantly enhancing the efficiency and precision of identifying and optimizing potential drug candidates. This article explores the various computational techniques utilized in drug design, including molecular docking, molecular dynamics (MD) simulations, free energy calculations, and virtual screening, and examines how these methods collectively contribute to the drug development process. The integration of these advanced simulations allows …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 24–29 Read article
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Sequence analysis, DNA Methylation and Molecular therapy of Oral cancer caused by Human Papilloma Virus
Abstract: DNA methylations with oral cancer are been associated with high-risk Human Papillomavirus (HPV) and Epstein-Barr Virus (EBV) onco-proteins interactions may cooperate to increase disease severity. The work focused on human papillomavirus strain 16, a high-risk, sexually transmitted responsible for 95% of all cervical cancers and a large portion of oropharyngeal cancers. The prediction of genes from has shown seven genes from HPV16 strain. Based on gene identification studies, Human papilloma …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 · pp. 1–9 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Precision Medicine for Neurofibromatosis Type 1: Progress and Prospects in Drug Discovery
Abstract: Objective: The development of neurofibromas, café-au-lait spots, and other neurological problems are the hallmarks of neurofibromatosis type 1 (NF1), a hereditary disorder. The dearth of efficacious pharmaceutical therapies underscores the need for novel therapeutic approaches, even in the face of clinical variability. Through very accurate prediction of the binding affinity of possible therapeutic drugs with the target protein, the computational technique known as “molecular docking” has become a potent tool …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 01–15 Read article
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Molecular Pharmacokinetics and Structural Docking of Phenolic Acids for Targeting NF-κB Pathway Components in Inflammation and Fibrosis: A Computational Approach Toward Therapeutic Discovery
Abstract: Inflammation and Fibrosis are critical pathological processes associated with various chronic diseases, often mediated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway. This study investigates the therapeutic potential of phenolic acids as modulators of the NF-κB pathway, aiming to identify novel ligands that can effectively interact with key components of this signaling cascade. A comprehensive computational approach was employed, utilizing molecular docking, pharmacological screening, and post-docking …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 14–31 Read article
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The Role of Artificial Intelligence and Machine Learning in Redefining Global Healthcare Systems and Advancing Medical Innovation
Abstract: Health Services are being revolutionized with AI and ML through improved accuracy, efficiency and accessibility in the delivery of health care. With AI and ML, it is now possible for health care professionals to assess varying amounts of complex clinical data in a relatively short amount of time, therefore, creating opportunities for early detection of disease, increasing the odds of accurate diagnosis, and improving the ability to make informed clinical …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 14–19 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Integrating Biotechnology, Physiology, and Agroecological Practices for Sustainable Crop Production and Protection
Abstract: Global agriculture is currently confronting a wide range of complex challenges, including a rapidly growing population, climate change, increasing pest and disease pressures, soil degradation, water scarcity, and the urgent need for sustainable intensification of crop production. Addressing these issues requires integrated strategies that combine crop improvement (through modern breeding and biotechnology), precision agronomic practices related to soil, irrigation, and nutrition, as well as advancements in plant physiology, molecular biology, …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Using Multitarget Molecular Docking to Examine the Antiviral Potential of Clerodendrum Phlomidis against Measles
Abstract: Objective: Measles, a viral disease caused by a member of the Paramyxoviridae virus family, is highly contagious and characterized by a respiratory illness and a maculopapular rash on the skin. Children are the main victims of the illness. In the context of drug development, this study investigates the efficacy of phytocompounds derived from Clerodendrum phlomidis against the target protein of the measles virus. Methods: The 7SKS protein was retrieved from …
Published in International Journal of Molecular Biotechnological Research · Vol. 1, Issue 2, 2023 · pp. 32–42 Read article
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Targeting Vasopressin 2 Receptor (V2R) in Renal Cystogenesis by Exploring the Nephroprotective Potential of “Terminalia arjuna”
Abstract: Objectives: Autosomal dominant polycystic kidney disease (ADPKD) is the most common inherited kidney disorder, leading to the formation of multiple cysts in the kidneys. It is a major cause of end-stage renal disease (ESRD), which often requires dialysis or a kidney transplant for survival. This research focuses on identifying potential bioactive compounds derived from natural sources that show promise for drug development targeting the V2R gene. Methods: The naturally occurred …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 2, 2024 · pp. 14–24 Read article
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Study of Lipid Profile and Its Correlation with Coronary Angiogram Finding in a Tertiary Care Hospital in an Urban Setting
Abstract: Coronary artery disease (CAD) is a major global health concern caused by the constriction or blockage of the coronary arteries, which can result in serious cardiovascular events. This study looks at the relationship between lipid profiles and the severity of CAD as measured by coronary angiography in patients in a tertiary care hospital. The study focuses on dyslipidemia as a major risk factor for CAD, emphasizing the importance of efficient …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 106–118 Read article