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Related Experiment Video

Updated: Sep 27, 2025

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
05:33

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

Published on: July 11, 2025

322

[Artificial intelligence: a solution for the lack of pathologists?]

Philipp Jurmeister1,2, Klaus-Robert Müller3,4, Frederick Klauschen5,6,7,8

  • 1Pathologisches Institut, Ludwig-Maximilians-Universität München, Thalkirchner Str. 36, 80337, München, Deutschland.

Der Pathologe
|April 11, 2022
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) will significantly change pathological diagnostics, but its role as a tool versus a replacement for human expertise is still unclear. Current AI excels at simple tasks, but complex histopathology requires further development.

Keywords:
Artificial intelligenceDigital pathologyImmunohistochemistryMachine LearningMolecular pathology

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Area of Science:

  • Pathology
  • Medical Diagnostics
  • Artificial Intelligence

Background:

  • Artificial intelligence (AI) is rapidly advancing and poised to significantly impact pathological diagnostics.
  • The extent to which AI will augment or replace human expertise in pathology remains an open question.
  • Current AI applications in histopathology often address simpler diagnostic challenges.

Purpose of the Study:

  • To evaluate the current and future impact of artificial intelligence on pathological diagnostics.
  • To explore whether AI will serve as an additional diagnostic tool or replace human pathologists.
  • To assess the capability of AI in handling complex histopathological diagnoses and differential diagnoses.

Main Methods:

  • Review of current literature on AI in histopathology and molecular pathology.
  • Analysis of the complexity of diagnostic tasks addressed by existing AI methods.
  • Discussion of the potential for AI in addressing difficult histomorphological differential diagnoses.

Main Results:

  • AI is expected to substantially impact pathological diagnostics.
  • Most current AI studies focus on relatively simple diagnostic problems, not routine diagnostic complexity.
  • AI is already indispensable in some molecular pathology methods.
  • The ability of AI to assist with complex histomorphological differential diagnoses is yet to be demonstrated.

Conclusions:

  • AI's role in pathology is evolving, with current limitations in handling complex cases.
  • Further research is needed to determine if AI will supplement or supplant human expertise in challenging diagnostic scenarios.
  • AI shows promise, particularly in molecular pathology, but its broader application in histomorphological diagnosis requires further validation.