Construction of Risk Prediction Model of Type 2 Diabetic Kidney Disease Based on Deep Learning.

IF 6.8 2区医学 Q1 ENDOCRINOLOGY & METABOLISM

Diabetes & Metabolism Journal Pub Date : 2024-04-30 DOI:10.4093/dmj.2023.0033

Chuan Yun, Fangli Tang, Zhenxiu Gao, Wenjun Wang, Fang Bai, Joshua D Miller, Huanhuan Liu, Yaujiunn Lee, Qingqing Lou

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.

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基于深度学习的 2 型糖尿病肾病风险预测模型的构建

本研究旨在利用长短期记忆（LSTM）神经网络开发糖尿病肾病（DKD）预测模型，并利用准确度、精确度、召回率和接收者操作特征曲线（ROC）下面积（AUC）评估其性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Diabetes & Metabolism Journal Medicine-Endocrinology, Diabetes and Metabolism

CiteScore

10.40

自引率

6.80%

发文量

审稿时长

52 weeks

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.