An overview of artificial intelligence applications for next-generation gynaecological pathology
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With the drive to roll out digital pathology in the UK, implementation of artificial intelligence (AI) tools for pathology is now a possibility, bringing with it the potential to change how we work as a specialty. AI promises many benefits for working practices such as improved efficiency and consistency, financial and productivity gains and ultimately a better service for our patients. Gynaecological pathology is a diverse specialty with many potential avenues for algorithm development, yet there are relatively few nearing clinical validation compared to other pathology specialties. This article provides a summary of the current landscape of AI in pathology with a focus on applications in gynaecological pathology. We discuss the ways pathologists can be involved in algorithm development and draw on our significant experiences in a nationally funded programme for AI development and research. Finally we look to what the future might hold.
Bell , S , Blackwood , J D , Fell , C , Mohammadi , M , Morrison , D , Harris-Birtill , D & Bryson , G 2023 , ' An overview of artificial intelligence applications for next-generation gynaecological pathology ' , Diagnostic Histopathology , vol. 29 , no. 10 , pp. 442-449 . https://doi.org/10.1016/j.mpdhp.2023.07.002
Copyright © 2023 the Publisher/the Authors. This work has been made available online in accordance with the Rights Retention Strategy This accepted manuscript is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The final published version of this work is available at https://doi.org/https://doi.org/10.1016/j.mpdhp.2023.07.002.
DescriptionFunding: The work described in the section Creation of a Scottish ‘living lab’ for AI development is part of iCAIRD which is funded by Innovate UK on behalf of UK Research and Innovation (UKRI), project number 104690.
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