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AI-based pathomics in kidney diseases: progress and application.
Runmin Ding1,2, Zexin Yang3,4, Qiqin Yu1,2
1Department of Urology, The Second Afffliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, China.
Renal Failure
|December 17, 2025
Summary
Artificial intelligence (AI) in pathomics revolutionizes renal pathology with quantitative image analysis for diagnosis. Challenges remain in data annotation and validation, but future integration promises improved patient care.
Area of Science:
- Nephrology
- Computational Pathology
- Artificial Intelligence
Background:
- Artificial intelligence (AI) is transforming pathological image analysis in renal pathology.
- AI-based pathomics enables high-throughput, machine-readable datasets for quantitative analysis and precise diagnosis.
Purpose of the Study:
- To explore the innovative applications of AI-based pathomics in nephrology.
- To identify current challenges and future directions for AI in renal pathology.
Main Methods:
- Quantitative analysis of pathological images using AI algorithms.
- Development of sophisticated tools for specific renal pathology tasks.
Main Results:
- AI tools aid in detecting glomerular injury, evaluating fibrosis, monitoring transplant pathology, and predicting renal tumor outcomes.
- Significant advancements in precision diagnosis and outcome prediction.
Conclusions:
- AI-based pathomics offers innovative approaches to renal pathology.
- Addressing challenges like data annotation, interpretability, and validation is crucial for clinical integration.
- Future research focusing on multi-omics integration and collaboration will enhance AI's role in nephrology for improved patient care.
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