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[Standardizing breast cancer digital pathology databases for artificial intelligence: practice and reflection].

F L Li1, H Bu1, Z Zhang1

  • 1Department of Pathology, West China Hospital, Sichuan University; Institute of Clinical Pathology, West China Hospital, Sichuan University, Chengdu 610041, China.

Zhonghua Bing Li Xue Za Zhi = Chinese Journal of Pathology
|March 8, 2026
PubMed
Summary
This summary is machine-generated.

Developing high-quality, standardized digital pathology databases is crucial for advancing artificial intelligence in diagnostics. This study outlines a pilot breast pathology database project, addressing key challenges for future development.

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Area of Science:

  • Pathology
  • Medical Informatics
  • Artificial Intelligence

Background:

  • Traditional pathology diagnosis struggles with data fragmentation and inefficiency.
  • The era of big data and artificial intelligence demands digital transformation in pathology.
  • High-quality, standardized databases are essential for digital pathology advancements.

Purpose of the Study:

  • To review global efforts in digital pathology database construction.
  • To detail a pilot project for a specialized breast pathology database.
  • To address challenges and inspire standardization for digital pathology and AI in China.

Main Methods:

  • Case enrollment and systematic data collection for a breast pathology database.
  • Standardized whole slide imaging (WSI) digitization protocols.
  • Discussion of critical issues: data schema, multi-center integration, scanning, and collaboration.

Main Results:

  • A pilot breast pathology database was developed.
  • Key considerations for database construction and integration were identified.
  • A framework for collaborative development and standardization was explored.

Conclusions:

  • Standardized digital pathology databases are vital for AI development.
  • Addressing data schema, integration, and collaboration is key to success.
  • The pilot project provides insights for sustainable digital pathology in China.