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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
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Artificial intelligence in renal pathology: Current status and future
1Department of Nephrology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, China; National Clinical Research Center for Child Health, Hangzhou, China.
Biomolecules & Biomedicine
|November 15, 2022
Summary
Artificial intelligence (AI) offers a promising solution for renal pathology diagnosis, addressing shortages of experts. AI, particularly deep learning, enhances the accuracy of kidney disease detection, classification, and outcome prediction from pathology images.
Area of Science:
- Nephrology
- Digital Pathology
- Artificial Intelligence
Background:
- Renal biopsy pathology is the gold standard for diagnosing kidney diseases.
- Increasing kidney disease incidence and pathologist shortages necessitate new diagnostic models.
- Digitization of pathology slides combined with AI presents a solution for accurate diagnosis.
Purpose of the Study:
- To review current and future applications of AI in renal pathology.
- To highlight AI's role in analyzing renal pathology images and predictive modeling.
- To discuss challenges and future perspectives of AI implementation in renal pathology.
Main Methods:
- Narrative review of AI methods in renal pathology.
- Discussion of diagnostic and prognostic applications of AI.
- Emphasis on AI in renal pathology images, predictive models, and 3D pathology.
Main Results:
- AI, especially deep learning, shows significant potential in renal pathology.
- AI applications span accurate detection, classification, and outcome prediction.
- AI can analyze complex features from digital pathology slides.
Conclusions:
- AI platforms are poised to transform renal pathology diagnostics and prognostics.
- Addressing implementation challenges is crucial for widespread AI adoption.
- AI integration promises improved accuracy and efficiency in kidney disease management.
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