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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
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Ethical issues in computational pathology.

Tom Sorell1, Nasir Rajpoot2, Clare Verrill3

  • 1PAIS, University of Warwick, Coventry, UK t.e.sorell@warwick.ac.uk.

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Summary
This summary is machine-generated.

This study examines ethical challenges in computational pathology, focusing on data privacy, AI explainability, and industry influence. Most identified ethical issues in whole slide imaging are found to be resolvable.

Keywords:
human tissueinformation technologypathologyscientific research

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Area of Science:

  • Digital pathology
  • Medical ethics
  • Artificial intelligence in medicine

Background:

  • Whole slide imaging (WSI) has advanced computational pathology.
  • Ethical considerations are crucial for AI integration in healthcare.

Purpose of the Study:

  • To explore ethical issues in WSI-based computational pathology.
  • To address tensions between AI data needs and data protection.
  • To examine data fusion, AI explainability, and industry influence.

Main Methods:

  • Literature review of WSI advances.
  • Analysis of ethical challenges in data collection, fusion, and AI.
  • Discussion of potential resolutions for identified ethical problems.

Main Results:

  • Ethical issues arise from data minimization conflicts, data fusion norms, AI 'black box' problems, and manufacturer interests.
  • The study identifies specific ethical tensions in computational pathology.

Conclusions:

  • Most ethical issues identified in whole slide image-based computational pathology are resolvable.
  • Proactive ethical frameworks can guide responsible AI implementation in pathology.