{"title":"Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.","authors":"Chuan Yun, Fangli Tang, Zhenxiu Gao, Wenjun Wang, Fang Bai, Joshua D Miller, Huanhuan Liu, Yaujiunn Lee, Qingqing Lou","doi":"10.4093/dmj.2023.0033","DOIUrl":null,"url":null,"abstract":"This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.","PeriodicalId":11153,"journal":{"name":"Diabetes & Metabolism Journal","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Diabetes & Metabolism Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.4093/dmj.2023.0033","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
This study aimed to develop a diabetic kidney disease (DKD) prediction model using long short term memory (LSTM) neural network and evaluate its performance using accuracy, precision, recall, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve.
期刊介绍：
The aims of the Diabetes & Metabolism Journal are to contribute to the cure of and education about diabetes mellitus, and the advancement of diabetology through the sharing of scientific information on the latest developments in diabetology among members of the Korean Diabetes Association and other international societies.
The Journal publishes articles on basic and clinical studies, focusing on areas such as metabolism, epidemiology, pathogenesis, complications, and treatments relevant to diabetes mellitus. It also publishes articles covering obesity and cardiovascular disease. Articles on translational research and timely issues including ubiquitous care or new technology in the management of diabetes and metabolic disorders are welcome. In addition, genome research, meta-analysis, and randomized controlled studies are welcome for publication.
The editorial board invites articles from international research or clinical study groups. Publication is determined by the editors and peer reviewers, who are experts in their specific fields of diabetology.
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