Leveraging explainable AI and large-scale datasets for comprehensive classification of renal histologic types

Leveraging explainable AI and large-scale datasets for comprehensive classification of renal histologic types

Abstract Recently, as the number of cancer patients has increased, much research is being conducted for efficient treatment, including the use of artificial intelligence in genitourinary pathology. Recent research has focused largely on the classification of renal cell carcinoma subtypes. Nonetheles...

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Bibliographic Details
Main Authors: Seung Wan Moon, Jisup Kim, Young Jae Kim, Sung Hyun Kim, Chi Sung An, Kwang Gi Kim, Chan Kwon Jung
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Renal tumor classification
Deep learning
Multiple instance learning
Digital pathology
Online Access:https://doi.org/10.1038/s41598-025-85857-8
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https://doi.org/10.1038/s41598-025-85857-8

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