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68 articles for “Disease Prediction”
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Research ArticleOpen accessIn the abstractSemSimp: A Parametric Method for Evaluating the Semantic Similarity of Digital ResourcesAntonio De Nicola, Anna Formica, Ida Mele, Francesco TaglinoAbioui, H., Idarrou, A., Bouzit, A., & Mammass, D. (2018). Towards a Novel and Generic Approach for OWL Ontology Weighting. Procedia Computer Science, 127, 426–435. https://doi.org/10.1016/j.procs.2018.01.140 Adhikari, A., Dutta, B., Dutta, A., Mondal, D., & Singh, S. (2018). An intrinsic information content-based semantic similarity measure considering the disjoint common subsumers of concepts of an ontology. Journal of the Association for … …Journal of Computer Science, Vol. 20, Issue 8 · 27 May 2024 · 5,778 accessesView PDFCite
Research ArticleOpen accessIn the abstractA New Disease Index Based on Multi-Spectra of UAV to Estimate Cotton DiseaseBing Chen, Jing Wang, Qiong Wang et al.Verticillium wilt is a significant disease that affects cotton plants, which can lead to stunted growth and reduced yield. To address this, a multi-spectral comprehensive monitoring disease index model is developed using an Unmanned Aerial Vehicle (UAV) to monitor the severity of cotton Verticillium wilt. First, multi-spectral dates were collected from Hexacopter (HY-6X) and the phenotype disease grade of cotton … …American Journal of Biochemistry and Biotechnology, Vol. 19, Issue 4 · 25 Mar 2024 · 5,095 accessesView PDFCite
Research ArticleOpen accessIn the abstractFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,216 accessesView PDFCite
Research ArticleOpen accessIn the abstractBig Data Framework for Predicting Infectious Diseases to Improve Healthcare by Discovering New Symptom PatternsAmal Mohamed Mounir, Mohamed Ibrahim Marie, Laila Abd-ElhamidThe utilization of big data in infectious disease control represents a captivating opportunity, as these novel data streams offer the potential to enhance the timeliness of preventive measures. Various healthcare providers in both the public and private sectors generate, store, and analyse extensive datasets to enhance the quality of services they deliver. Recently, the outbreak of the new coronavirus, COVID-19, … …Journal of Computer Science, Vol. 20, Issue 10 · 2 Aug 2024 · 4,922 accessesView PDFCite
Research ArticleOpen accessIn the abstractWhale Optimized Deep Generative Adversarial Network Based Alzheimer's Stages Detection Using 3D MRI Brain NeuroimagingR. Sampath, M. BaskarAlzheimer's Disease (AD), a common, chronic neurodegenerative condition, is characterized by the loss of neurons and synapses in the cerebral cortex and specific subcortical regions. According to claims from a recent study, AD has a 20% misdiagnosis rate. Therefore, it is essential to create a useful tool to recognize the stages of AD with a lower prediction error rate to … …Journal of Computer Science, Vol. 19, Issue 8 · 4 Aug 2023 · 5,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Risk of Diabetes using a Model based on Multilayer Perceptron and Features ExtractionFrancesca Fallucchi, Alessandro CabroniDiabetes (diabetes mellitus) is a disease emerging when a person has a high blood sugar level for a prolonged period. In the healthcare context, one of the most important topic is the prevention of the disease. This study relates to diabetes prevention. In particular, it aims to produce random generated datasets according to a rule named Finnish Diabetes Risk Score … …Journal of Computer Science, Vol. 17, Issue 9 · 7 Sep 2021 · 6,588 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Tool for Testing Agreement Level on Continuous DatasetsBasavarajaiah Mariyappa Doddagangavadi, B. Narasimha Murthy, Netra RajpurohitVarious analytical studies explored the new innovation for testing agreement level in medical and life sciences which can be simulated by Cohen ‘κ’ based on the practical applications. From the past medical literature, many authors suggested that, there is some disproportion research gaps that exists in the statistical methods for measuring the agreements between two or more observers from ‘Cohen … …Current Research in Biostatistics, Vol. 11, Issue 1 · 19 May 2021 · 11,787 accessesView PDFCite
Research ArticleOpen accessIn the abstractKRLSMDA: Identifying Human miRNA–Disease Association Based on Similarity and Kronecker Regularized Least Squares MethodLingzhi Zhu, Weimin Gao, Guixiang Li et al.A growing number of studies have suggested that miRNAs (microRNAs) have associations with human diseases, the design and discovery of drug. But so far, we do not yet fully understand the molecular mechanism of miRNAs in the development of human diseases. Predicting miRNA-disease associations is helpful for understanding the molecular mechanism of miRNAs in the development of human diseases. However, … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 15 Mar 2021 · 6,408 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Microbe-Drug Association based on Similarity and Semi-Supervised LearningLingzhi Zhu, Jun Wang, Guixiang Li et al.Increasing clinic evidences have showed that microbial communities play important roles in human health and disease. Predicting hidden microbe-drug associations can be helpful in understanding the microbe-drug association mechanisms in clinical treatment, drug discovery, combinations and repositioning. Some computational methods were proposed to predict the associations of microbes and drugs. However, the prediction performance of these methods needs to be … …American Journal of Biochemistry and Biotechnology, Vol. 17, Issue 1 · 9 Mar 2021 · 7,539 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of Influential Nodes With Topological Structure Via GRAPH Neural Network (GNN) Approach in Social Media NetworksRajnish Kumar, Laxmi Ahuja, Suman Mann, Sanmukh KaurThe amount of data in social networks is vast these days, and constantly changing, making influential node identification crucial. The existing topologies are constantly changing due to the evolving behavior of the applied dataset. Node and leaf topology or feature-based value form the basis for machine learning and centrality computation. Hence, influential node value determination is based on the node … …Journal of Computer Science, Vol. 22, Issue 2 · 17 Feb 2026 · 1,836 accessesView PDFCite