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How to use AI in pathology.

Peter Schüffler1,2,3, Katja Steiger1, Wilko Weichert1

  • 1Institute of Pathology, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.

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Summary

Artificial intelligence (AI) offers significant benefits in pathology for both clinical practice and research. Transitioning to digital workflows is key for labs to leverage AI for improved patient care and biomarker discovery.

Keywords:
computational pathologydigital pathologypathology AI

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Area of Science:

  • Digital pathology
  • Computational pathology
  • Medical artificial intelligence (AI)

Background:

  • AI is increasingly vital in pathology, aiding daily tasks for pathologists and discovering novel biomarkers.
  • The full potential of AI in pathology is yet to be realized, as many labs still require digital workflow integration.

Purpose of the Study:

  • To outline the primary advantages of implementing AI in pathology.
  • To identify essential requirements for successful AI adoption in pathology.
  • To illustrate AI integration within a standard pathology workflow.

Main Methods:

  • This perspective piece reviews current literature and expert insights on AI in pathology.
  • It focuses on the practical aspects of AI implementation and its benefits.
  • Case examples and workflow illustrations are used to demonstrate AI application.

Main Results:

  • AI enhances diagnostic accuracy and efficiency in pathology.
  • Digitalization of pathology workflows is a prerequisite for AI implementation.
  • Key requirements include data infrastructure, standardization, and pathologist training.

Conclusions:

  • AI integration promises to revolutionize pathology, improving patient outcomes through advanced diagnostics and biomarker discovery.
  • A strategic transition to digital workflows is crucial for realizing AI's benefits.
  • Continued research and development are essential for widespread AI adoption in pathology.