Unleashing the potential of AI for pathology: challenges and recommendations

Author:

Asif Amina1ORCID,Rajpoot Kashif2,Graham Simon3,Snead David34,Minhas Fayyaz15,Rajpoot Nasir1356

Affiliation:

1. Tissue Image Analytics Centre, Department of Computer Science University of Warwick Coventry UK

2. School of Computer Science University of Birmingham Birmingham UK

3. Histofy Ltd, Birmingham Business Park Birmingham UK

4. Department of Pathology University Hospitals Coventry & Warwickshire NHS Trust Coventry UK

5. Cancer Research Centre University of Warwick Coventry UK

6. The Alan Turing Institute London UK

Abstract

AbstractComputational pathology is currently witnessing a surge in the development of AI techniques, offering promise for achieving breakthroughs and significantly impacting the practices of pathology and oncology. These AI methods bring with them the potential to revolutionize diagnostic pipelines as well as treatment planning and overall patient care. Numerous peer‐reviewed studies reporting remarkable performance across diverse tasks serve as a testimony to the potential of AI in the field. However, widespread adoption of these methods in clinical and pre‐clinical settings still remains a challenge. In this review article, we present a detailed analysis of the major obstacles encountered during the development of effective models and their deployment in practice. We aim to provide readers with an overview of the latest developments, assist them with insights into identifying some specific challenges that may require resolution, and suggest recommendations and potential future research directions. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Funder

Health Technology Assessment Programme

Publisher

Wiley

Subject

Pathology and Forensic Medicine

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