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Safety Precautions and Operating Procedures in an ABSL-4 Laboratory: 4. Medical Imaging Procedures

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Published on: October 3, 2016

Patient safety in AI-powered diagnostic pathology.

Massimo Rugge¹, Matteo Fraschini², Enrico Orvieto³

¹DIMED, Università degli Studi di Padova, Padova, Italy massimo.rugge@unipd.it.

Journal of Clinical Pathology

|November 6, 2025

Summary

This summary is machine-generated.

Artificial intelligence (AI) enhances diagnostic pathology accuracy but cannot replace human oversight. Implementing AI requires clear application domains and robust safety measures for patient well-being.

Keywords:

Artificial Intelligence Diagnostic Techniques and Procedures Patient Safety SAFETY

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

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Area of Science:

Pathology
Medical Informatics
Artificial Intelligence

Background:

Diagnostic pathology integrates traditional histology with artificial intelligence (AI) for enhanced accuracy.
AI in pathology involves digital image generation, algorithm training, dataset construction, validation, and output monitoring.
Current evidence indicates AI complements, but does not autonomously replace, human diagnostic capabilities.

Purpose of the Study:

To critically review current AI applications in diagnostic pathology.
To emphasize patient-centered safety considerations in AI implementation.
To highlight the need for collaborative regulatory measures for AI in pathology.

Main Methods:

Review of current scientific evidence on AI in diagnostic pathology.
Analysis of key steps in AI-powered diagnostic pathology workflow.
Examination of international healthcare recommendations for AI implementation.

Main Results:

AI can improve diagnostic accuracy but requires human supervision.
Generative intelligence presents new opportunities in pathology.
Clear definition of application domains and safety monitoring are crucial for clinical AI use.

Conclusions:

Patient safety is paramount in AI-powered diagnostic pathology.
Collaborative efforts are essential for developing safety-oriented regulatory measures.
International cooperation among stakeholders is necessary for responsible AI deployment in pathology.