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Updated: Sep 11, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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Artificial Intelligence in Pathology: Advancing Large Models for Scalable Applications.

Zhiping Xiao1, Bin Feng2, Junwei Yang2

  • 1Department of Computer Science and Engineering, University of Washington, Seattle, Washington, USA; email: patxiao@uw.edu, swang@cs.washington.edu.

Annual Review of Biomedical Data Science
|August 11, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) is transforming medical research, particularly in pathology. This review highlights AI datasets and models, paving the way for large-scale applications while noting ethical considerations.

Keywords:
artificial intelligencedeep learningensemble modelsfoundation modelsmachine learningmedical datasetspathology

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Area of Science:

  • Medical research
  • Pathology
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) has a long history of supporting pathology studies.
  • Recent advancements include the development of pathology foundation models and pathology ensemble models.
  • These large-scale models build upon previous AI innovations in the field.

Purpose of the Study:

  • To review AI datasets and models relevant to pathology.
  • To explore the emergence and impact of large-scale AI models in pathology.
  • To discuss the ethical implications of AI in sensitive medical applications.

Main Methods:

  • Literature review of AI datasets and models in pathology.
  • Analysis of the historical development and current trends of AI in pathology.
  • Discussion of ethical concerns, including privacy risks.

Main Results:

  • AI significantly enhances pathology studies, offering new research possibilities.
  • The development of large-scale AI models is a recent trend in pathology.
  • Ethical considerations, such as privacy, are critical for AI implementation.

Conclusions:

  • AI, including large models, is crucial for advancing pathology research.
  • A comprehensive understanding of available datasets and models is essential for future applications.
  • Balancing AI innovation with ethical considerations is paramount for responsible implementation in medicine.