Artificial intelligence empowers kidney disease research:mechanism exploration and treatment optimization
MENG Lingzhang
YANG Mingyue
XIONG Lijia
WEI Suosu
HUANG Xiaoyuan
LIANG Huaqian
MAO Xiuli
ZHANG Xiamin
LIN Wenxian
YE Kun
Abstract：Kidney diseases pose one of the major burdens on global public health,and their incidence and mortality continue to rise.The rapid development of artificial intelligence(AI)provides revolutionary tools for exploring the mechanisms of kidney diseases and optimizing clinical treatments.This review summarizes the main types of kidney diseases and their complex pathogenic mechanisms,and points out the limitations of traditional research methods,and elaborates on the applications of AI in multi-omics data analysis,pathological image recognition in kidney diseases,big data-driven risk prediction,and mechanism analysis of rare kidney diseases.In clinical treatments,AI assists early screening,optimizations of individualized nutrition and dialysis,management of prognosis,and kidney transplant matching,significantly improving diagnostic accuracy and patient prognosis.This review also analyzes the challenges faced by AI and looks forward to the future prospects of multimodal fusion,federated learning,and large language models in precision medicine for kidney diseases.
Keywords：Kidney diseasesArtificial intelligence(AI)PathogenesisClinical treatment
Publication Date：2025-12-30
Online Publishing Date：2026-01-16(First online date of this platform, not the publication date of the document)
Pages：5( 1349-1353 )