Search Results - "Uhmn, Saangyong"
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A Prediction Model Using Machine Learning Algorithm for Assessing Stone-Free Status after Single Session Shock Wave Lithotripsy to Treat Ureteral Stones
Published in The Journal of urology (01-12-2018)“…The aim of this study was to develop and validate a decision support model using a machine learning algorithm to predict treatment success after single session…”
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Journal Article -
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Male-specific genetic effect on hypertension and metabolic disorders
Published in Human genetics (01-03-2014)“…Genetic risk factors for hypertension may have age or gender specificity and pleiotropic effects. This study aims to measure the risk of genetic and…”
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Journal Article -
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A Novel Deep Learning–based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography
Published in European urology focus (11-07-2024)“…Our novel artificial intelligence system, which uses advanced deep learning, facilitated diagnosis of urolithiasis with 94% accuracy and three times faster…”
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Journal Article -
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Chronic Hepatitis Classification Using SNP Data and Data Mining Techniques
Published in 2007 Frontiers in the Convergence of Bioscience and Information Technologies (01-10-2007)“…The machine learning techniques, SVM, decision tree, and decision rule, are used to predict the susceptibility to the liver disease, chronic hepatitis from…”
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Conference Proceeding -
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A study on application of single nucleotide polymorphism and machine learning techniques to diagnosis of chronic hepatitis
Published in Expert systems (01-02-2009)“…: We used several machine learning techniques to predict the susceptibility to chronic hepatitis from single nucleotide polymorphism (SNP) data. These are…”
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Journal Article -
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Predicting Susceptibility to Chronic Hepatitis using Single Nucleotide Polymorphism Data and Support Vector Machine
Published in 2006 International Conference on Hybrid Information Technology (01-11-2006)“…SVM(Support VectorMachine) is used to predict the susceptibility to Chronic Hepatitis from SNP(single nucleotide polymorphism) data. SVM is trained to predict…”
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Conference Proceeding