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Application and Progress of Artificial Intelligence in Prognosis of Kidney Diseases
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Xuan ZHANG1, Yu XIE2, Yaning FENG2, Mengyu LIANG1, Li GAO1, Qin ZHU1
Chinese Archives of Traditional Chinese Medicine | 2025, 43(12) : 15 - 20
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Chinese Archives of Traditional Chinese Medicine | 2025, 43(12): 15-20
• Digital Traditional Chinese Medicine •
Application and Progress of Artificial Intelligence in Prognosis of Kidney Diseases
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Xuan ZHANG1, Yu XIE2, Yaning FENG2, Mengyu LIANG1, Li GAO1, Qin ZHU1
Affiliations
  • 1.Hangzhou Hospital of Traditional Chinese Medicine，Hangzhou 310000，Zhejiang，China
  • 2.Zhejiang Chinese Medical University，Hangzhou 310000，Zhejiang，China
Published: 2025-12-10 doi: 10.13193/j.issn.1673-7717.2025.12.003
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The incidence of kidney diseases worldwide are increasing year by year.Due to the low early diagnosis rate and the lack of long-term effective scientific management，some patients progress rapidly to end-stage renal disease，which brings a heavy burden to families and society and has become an urgent public health issue that needs the attention.Nowadays，the application value and development space of the“artificial intelligence+medicine”model in the prevention，diagnosis，treatment and management of clinical diseases are increasingly evident.Artificial intelligence（AI）can not only help clinical workers diagnose kidney diseases，but also make risk predictions，identify early risk factors and have huge predictive value for the prognosis of kidney diseases.This review summarized the application and progress of artificial intelligence in predicting the prognosis of kidney diseases in recent years，with the aim of contributing to the prediction and control of clinical prognosis.

artificial intelligence  /  kidney disease  /  machine learning  /  neural networks  /  random forests
Xuan ZHANG, Yu XIE, Yaning FENG, Mengyu LIANG, Li GAO, Qin ZHU. Application and Progress of Artificial Intelligence in Prognosis of Kidney Diseases[J]. Chinese Archives of Traditional Chinese Medicine, 2025 , 43 (12) : 15 -20 . DOI: 10.13193/j.issn.1673-7717.2025.12.003
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Year 2025 volume 43 Issue 12
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doi: 10.13193/j.issn.1673-7717.2025.12.003
  • Online Date：2026-04-29
  • Published：2025-12-10
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    1.Hangzhou Hospital of Traditional Chinese Medicine，Hangzhou 310000，Zhejiang，China
    2.Zhejiang Chinese Medical University，Hangzhou 310000，Zhejiang，China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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