Public evidence on AI products for digital pathology

Novel products applying artificial intelligence (AI)-based methods to digital pathology images are touted to have many uses and benefits. However, publicly available information for products can be variable, with few sources of independent evidence. This review aimed to identify public evidence for AI-based products for digital pathology. Key features of products on the European Economic Area/Great Britain (EEA/GB) markets were examined, including their regulatory approval, intended use, and published validation studies. There were 26 AI-based products that met the inclusion criteria and, of these, 24 had received regulatory approval via the self-certification route as General in vitro diagnostic (IVD) medical devices. Only 10 of the products (38%) had peer-reviewed internal validation studies and 11 products (42%) had peer-reviewed external validation studies. To support transparency an online register was developed using identified public evidence ( https://osf.io/gb84r/ ), which we anticipate will provide an accessible resource on novel devices and support decision making.

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Publication Details

Journal
npj Digital Medicine
Published
2024-10-25
DOI
https://doi.org/10.1038/s41746-024-01294-3
Citations
17
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
5.91

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article

Public evidence on AI products for digital pathology

Darren Treanor, Daljeet Bansal, Clare McGenity, Gillian A. Matthews
17 citations
npj Digital Medicine
AI in cancer detection
5.91
article

Public evidence on AI products for digital pathology

Darren Treanor, Daljeet Bansal, Clare McGenity, Gillian A. Matthews
article en
17 citations

Abstract

Novel products applying artificial intelligence (AI)-based methods to digital pathology images are touted to have many uses and benefits. However, publicly available information for products can be variable, with few sources of independent evidence. This review aimed to identify public evidence for AI-based products for digital pathology. Key features of products on the European Economic Area/Great Britain (EEA/GB) markets were examined, including their regulatory approval, intended use, and published validation studies. There were 26 AI-based products that met the inclusion criteria and, of these, 24 had received regulatory approval via the self-certification route as General in vitro diagnostic (IVD) medical devices. Only 10 of the products (38%) had peer-reviewed internal validation studies and 11 products (42%) had peer-reviewed external validation studies. To support transparency an online register was developed using identified public evidence ( https://osf.io/gb84r/ ), which we anticipate will provide an accessible resource on novel devices and support decision making.

npj Digital MedicineVol. 7(1)
Linköping University (SE), University of Leeds (GB), Leeds Teaching Hospitals NHS Trust (GB)
Nuclear Power Institute of China, UK Research and Innovation, Innovate UK
Openalex Percentile: Top 3%
AI in cancer detection
5.91
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