Research hotspots and frontiers of machine learning in renal medicine: a bibliometric and visual analysis from 2013 to 2024.

Journal: International urology and nephrology
Published Date:

Abstract

BACKGROUND: The kidney, an essential organ of the human body, can suffer pathological damage that can potentially have serious adverse consequences on the human body and even affect life. Furthermore, the majority of kidney-induced illnesses are frequently not readily identifiable in their early stages. Once they have progressed to a more advanced stage, they impact the individual's quality of life and burden the family and broader society. In recent years, to solve this challenge well, the application of machine learning techniques in renal medicine has received much attention from researchers, and many results have been achieved in disease diagnosis and prediction. Nevertheless, studies that have conducted a comprehensive bibliometric analysis of the field have yet to be identified.

Authors

  • Feng Li
    Department of General Surgery, Shanghai Traditional Chinese Medicine (TCM)-INTEGRATED Hospital of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
  • ChangHao Hu
    Department of Anesthesiology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
  • Xu Luo
    Southwest Hospital, Third Military Medical University, Chongqing, 400038 China.