A comprehensive AI model development framework for consistent Gleason grading

Background: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. Methods: We present a comprehensive digital pathology w...

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Bibliographic Details
Main Authors:	Huo, X, Ong, KH, Lau, KW, Gole, L, Young, DM, Tan, CL, Zhu, X, Zhang, C, Zhang, Y, Li, L, Han, H, Lu, H, Zhang, J, Hou, J, Zhao, H, Gan, H, Yin, L, Wang, X, Chen, X, Lv, H, Cao, H, Yu, X, Shi, Y, Huang, Z, Sanders, SJ
Format:	Journal article
Language:	English
Published:	Nature Research 2024

A comprehensive AI model development framework for consistent Gleason grading

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