68 results for “Disease Prediction”

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Research ArticleOpen accessIn the abstractAn Efficient Distributed Bioinformatics Computing System for DNA Sequence Analysis on Encoding SystemMohammad Ibrahim Khan, Chotan SheelThis study provides an effective design of search technique of a distributed bioinformatics computing system for analysis of DNA sequences using OPTSDNA algorithm. This system could be used for disease detection, criminal forensic analysis, gene prediction, genetic system and protein analysis. Different types of distributed algorithms for the search and identification for DNA segments and repeat pattern in a given … …Current Research in Bioinformatics, Vol. 2, Issue 2 · 20 Dec 2013 · 6,931 accessesView PDF Cite

Research ArticleOpen accessIn the abstractChildhood Cancer-a Hospital based study using Decision Tree TechniquesK. Kalaivani, R. ShanmugalakshmiProblem statement: Cancer is generally regarded as a disease of adults. But there being a higher proportion of childhood cancer (ALL-Acute Lymphoblastic Leukemia) in India. The incidence of childhood cancer has increased over the last 25 years, but the increase is much larger in females. The aim was to increase our understanding of the determinants of south Indian parental reactions … …Journal of Computer Science, Vol. 7, Issue 12 · 17 Oct 2011 · 7,057 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBridging from Cells to Cognition in Autism Pathophysiology: Biological Pathways to Defective Brain Function and PlasticityMatthew P. Anderson, Brian S. Hooker, Martha R. HerbertWe review evidence to support a model where the disease process underlying autism may begin when an in utero or early postnatal environmental, infectious, seizure, or autoimmune insult triggers an immune response that increases reactive oxygen species (ROS) production in the brain that leads to DNA damage (nuclear and mitochondrial) and metabolic enzyme blockade and that these inflammatory and oxidative … …American Journal of Biochemistry and Biotechnology, Vol. 4, Issue 2 · 30 Jun 2008 · 17,455 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAnimal Health Prediction Using Hybrid CNN Based BiLSTM Classification Model: A Deep Learning ApproachJ. Rathi, A. SumathiAccurate prediction of animal diseases is vital in veterinary medicine, as it can substantially enhance animal health outcomes and mitigate economic losses, making it a critical task that warrants attention and innovative solutions. This paper proposes a novel approach to animal condition classification, leveraging an Auto-encoder-based feature selection process and an Improved Hybrid Convolutional Neural Networks (CNN) with Bidirectional (Bi-LSTM) … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,481 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordComputational Prediction of Diabetic Nephropathy-Associated Comorbidities and Their Key Genes by Analyzing RNA-Seq DataChaity Paul, Md. Ashiq Uddin, Rupa Dey et al.Diabetic Nephropathy (DN) is a complex health condition that leads to various kidney diseases. According to the World Health Organization, over 2 million deaths have been reported due to diabetes and diabetes related kidney diseases in 2021. And at the recent 78th World Health Assembly, chronic kidney disease was reported to be one of the most common diabetes-related complications, and … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 19 May 2026 · 1,667 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordPost-COVID Impact Analysis and Effective Recommendation Solutions Over Risk Prediction Using Hybrid ModelBoddeti Jaggan Mohan Ravi Kumar, P. V. G. D. Prasad Reddy, G SrinivasThe COVID-19 pandemic (2019-2022) resulted in significant global mortality, largely attributed to the virus's unpredictable pathophysiology, rapid disease progression affecting multiple organ systems, and initial lack of effective treatments. This study systematically examines post-COVID-19 complications across major organ systems, including respiratory dysfunction, cardiovascular complications, renal disorders, musculoskeletal pain, gastrointestinal disturbances, neurological sequelae, alopecia, endocrine and metabolic dysregulation, and mental health … …Journal of Computer Science, Vol. 21, Issue 11 · 23 Dec 2025 · 1,643 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordUPLC-Q-Exactive Orbitrap-MS Analysis of Anchusa italica Retz. Flowers: Molecular Docking, Dynamics Modeling, and Pharmacokinetics for Cardiovascular DiseaseLinyang Wang, Yan Chen, Ainiwaer Aikemu, Shuge TianThis study builds on prior UPLC-Q-Exactive Orbit rap-MS analyses of Anchusa italica Retz. Flowers (Airfs) to explore their anti-cardiovascular mechanis·ms and key bioactive markers. UPLC-Q-Exactive Orbitrap-MS identified 30 major compounds, including polyphenols and flavonoids with strong antioxidant activity. The potential active ingredients were then screened using Lipinski's rule of five, and a network pharmacology method was employed to construct an … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Oct 2025 · 2,599 accessesView PDF Cite