| 李寒笑,曾甜,邢雨,朱好辉.机器学习用于慢性肾衰竭研究进展[J].中国医学影像技术,2024,40(4):614~617 |
| 机器学习用于慢性肾衰竭研究进展 |
| Application progresses of machine learning in chronic renal failure |
| 投稿时间：2023-11-05 修订日期：2024-01-11 |
| DOI：10.13929/j.issn.1003-3289.2024.04.029 |
| 中文关键词: 机器学习 肾衰竭,慢性 诊断 预后 |
| 英文关键词:machine learning kidney failure, chronic diagnosis prognosis |
| 基金项目:国家自然科学基金面上项目(82371980)、2021年度河南省卫生健康中青年学科带头人培养项目。 |
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| 中文摘要: |
| 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。 |
| 英文摘要: |
| 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. |
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