Application progress of machine learning in kidney disease.
10.3760/cma.j.cn121430-20221212-01085
- Author:
Pingping WANG
1
;
Kedan CAI
2
Author Information
1. Health Science Center, Ningbo University, Ningbo 315000, Zhejiang, China.
2. Department of Nephrology, Ningbo No.2 Hospital, Ningbo 315000, Zhejiang, China. Corresponding author: Cai Kedan, Email: caikedan_1983@126.com.
- Publication Type:Journal Article
- MeSH:
Humans;
Artificial Intelligence;
Machine Learning;
Kidney;
Kidney Diseases/diagnosis*
- From:
Chinese Critical Care Medicine
2023;35(12):1331-1334
- CountryChina
- Language:Chinese
-
Abstract:
Kidney disease affects a large number of people around the world, imposing a significant burden to people's health and life. If early prediction, rapid diagnosis and prognosis prediction of kidney disease can be carried out, the health of patients will be better protected. Machine learning belongs to the category of artificial intelligence, which can be divided into supervised learning, unsupervised learning and reinforcement learning. With the increasing requirements for the processing and analyzing large-scale and high-dimensional data, machine learning is playing an increasingly important role in the medical domain, and the field of kidney disease is no exception. This article presents a comprehensive overview of the application progress of machine learning in kidney disease, aiming to make medical staff's decision-making in kidney disease more early, accurate and rapid, and better escort the life and health of patients.
