机器学习用于慢性肾衰竭研究进展
Application progresses of machine learning in chronic renal failure
李寒笑 1曾甜 2邢雨 2朱好辉2
作者信息
- 1. 新乡医学院研究生院,河南 新乡 435000;河南省人民医院超声科,河南 郑州 450003
- 2. 河南省人民医院超声科,河南 郑州 450003
- 折叠
摘要
慢性肾衰竭(CRF)为多因素所致慢性进行性肾实质损害,进而可累及全身多系统.机器学习(ML)可对高维医学数据进行数据分析和挖掘,对于解决临床复杂问题具有显著潜力.本文围绕ML用于CRF研究进展进行综述.
Abstract
Chronic renal failure(CRF)represents chronic progressive renal parenchyma damage caused by multiple factors,which might involve various systems of patients.Machine learning(ML)has shown significant potential for solving complex clinical problems due to its ability of data analysis and data mining for high-dimensional medical data.The application progresses of ML in CRF were reviewed in this article.
关键词
机器学习/肾衰竭,慢性/诊断/预后Key words
machine learning/kidney failure,chronic/diagnosis/prognosis引用本文复制引用
基金项目
国家自然科学基金面上项目(82371980)
河南省卫生健康中青年学科带头人培养项目(2021)()
出版年
2024
NETL
NSTL
万方数据