ARTIFICIAL INTELLIGENCE IN KIDNEY DISEASE: A COMPREHENSIVE STUDY AND BIBLIOMETRIC ANALYSIS

Authors

  • Hinata Shakeel
  • Prof. Sonal Sood

Keywords:

AI, ML, IDH, Big data, MAP, HR, UFR, DBP

Abstract

This paper advances our knowledge of how artificial intelligence is influencing nephrology by fusing bibliometric methods with a narrative synthesis. It provides evidence-based insights that can help drive the creation of policies, assist academic research, and improve clinical practice. Additionally, it emphasizes how AI has the potential to revolutionize kidney treatment, cut down on diagnostic delays, and improve patient outcomes—particularly in environments with limited resources.

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Published

2025-11-04

How to Cite

Hinata Shakeel, & Prof. Sonal Sood. (2025). ARTIFICIAL INTELLIGENCE IN KIDNEY DISEASE: A COMPREHENSIVE STUDY AND BIBLIOMETRIC ANALYSIS. Utilitas Mathematica, 122(2), 2428–2441. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/2996

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