# Artificial Intelligence in Nephrology: From Early Detection to Clinical Management of Kidney Diseases

## TL;DR

This paper reviews how artificial intelligence is being used in kidney disease detection and treatment, highlighting its potential to improve diagnosis and therapy optimization.

## Contribution

The paper provides a comprehensive review of AI applications in nephrology, emphasizing gaps in therapy optimization and the need for accessible AI solutions.

## Key findings

- AI models show high accuracy (≥ 90%) in predicting kidney diseases early.
- Fewer studies focus on therapy optimization, with moderate-to-high performance (≃ 85%).
- Developing accessible AI solutions for all kidney disease stages is crucial for better patient care.

## Abstract

Artificial Intelligence (AI) is transforming the healthcare field, offering innovative tools for improving the prediction, detection, and management of diseases. In nephrology, AI holds the potential to improve the diagnosis and treatment of kidney diseases, as well as the optimization of renal replacement therapies. In this review, a comprehensive analysis of recent literature works on artificial intelligence applied to nephrology is presented. Two key research areas structure this review. The first section examines AI models used to support early prediction of acute and chronic kidney disease. The second section explores artificial intelligence applications for hemodialytic therapies in renal insufficiency. Most studies reported high accuracy (e.g., accuracy ≥ 90%) in early prediction of kidney diseases, while fewer addressed therapy optimization and complication prevention, typically reporting moderate-to-high performance (e.g., accuracy ≃ 85%). Filling this gap and developing more accessible AI solutions that address all stages of kidney disease would therefore be crucial to support physicians’ decision-making and improve patient care.