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Artificial intelligence and perspective for rare genetic kidney diseases.

Chen Xiaoyi1, Burgun Anita2, Boyer Olivia3

  • 1Université Paris Cité, Imagine Institute, Data Science Platform, INSERM UMR 1163, Paris, France.

Kidney International
|June 22, 2025
PubMed
Summary

Artificial intelligence (AI) offers transformative potential for rare kidney diseases by overcoming data scarcity and complexity. AI aids in disease characterization, gene discovery, and improving patient diagnostic journeys.

Keywords:
artificial intelligenceclinical decision supportdisease characterizationhypothesis generationrare genetic kidney disease

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Area of Science:

  • Biomedicine
  • Nephrology
  • Artificial Intelligence

Background:

  • Big data and AI integration are revolutionizing biomedicine, but AI applications in nephrology are challenged by complex disease mechanisms and physiology.
  • Rare kidney diseases, affecting fewer than 1 in 2000 people, present additional hurdles due to data scarcity and clinical complexities, hindering accurate AI-driven disease characterization and prediction.
  • Over 150 rare kidney conditions exhibit significant genetic and clinical heterogeneity, posing unique challenges for AI implementation.

Purpose of the Study:

  • To explore the current landscape of AI applications in rare genetic kidney diseases.
  • To examine key challenges and advancements in AI-driven disease characterization and clinical decision support for rare kidney conditions.
  • To highlight the role of AI, particularly unsupervised and generative methods, in hypothesis generation for rare kidney diseases.

Main Methods:

  • Review of recent literature on AI applications in nephrology, focusing on big data, decision support, imaging, multi-omics, and genotype-phenotype analysis.
  • Examination of AI's role in addressing data scarcity and clinical complexities in rare genetic kidney diseases.
  • Emphasis on unsupervised learning and generative AI for hypothesis generation and pattern identification.

Main Results:

  • AI can empower physicians to interpret complex datasets in rare kidney diseases.
  • AI facilitates the identification of patterns and generation of insights for improved patient outcomes.
  • AI contributes to innovative medical research by uncovering novel genes and pathways relevant to both rare and common diseases.

Conclusions:

  • AI is essential for advancing rare kidney disease research and care.
  • AI can significantly shorten the diagnostic odyssey for patients with rare kidney conditions.
  • AI integration promises improved patient outcomes and accelerated discovery in rare genetic kidney diseases.