Examining labelling guidelines for AI-based software as a medical device : A review and analysis of dermatology mobile applications in Australia
(2024) In Australasian Journal of Dermatology- Abstract
In recent years, there has been a surge in the development of AI-based Software as a Medical Device (SaMD), particularly in visual specialties such as dermatology. In Australia, the Therapeutic Goods Administration (TGA) regulates AI-based SaMD to ensure its safe use. Proper labelling of these devices is crucial to ensure that healthcare professionals and the general public understand how to use them and interpret results accurately. However, guidelines for labelling AI-based SaMD in dermatology are lacking, which may result in products failing to provide essential information about algorithm development and performance metrics. This review examines existing labelling guidelines for AI-based SaMD across visual medical specialties, with... (More)
In recent years, there has been a surge in the development of AI-based Software as a Medical Device (SaMD), particularly in visual specialties such as dermatology. In Australia, the Therapeutic Goods Administration (TGA) regulates AI-based SaMD to ensure its safe use. Proper labelling of these devices is crucial to ensure that healthcare professionals and the general public understand how to use them and interpret results accurately. However, guidelines for labelling AI-based SaMD in dermatology are lacking, which may result in products failing to provide essential information about algorithm development and performance metrics. This review examines existing labelling guidelines for AI-based SaMD across visual medical specialties, with a specific focus on dermatology. Common recommendations for labelling are identified and applied to currently available dermatology AI-based SaMD mobile applications to determine usage of these labels. Of the 21 AI-based SaMD mobile applications identified, none fully comply with common labelling recommendations. Results highlight the need for standardized labelling guidelines. Ensuring transparency and accessibility of information is essential for the safe integration of AI into health care and preventing potential risks associated with inaccurate clinical decisions.
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- author
- Oloruntoba, Ayooluwatomiwa ; Ingvar, Åsa LU ; Sashindranath, Maithili ; Anthony, Ojochonu ; Abbott, Lisa ; Guitera, Pascale ; Caccetta, Tony ; Janda, Monika ; Soyer, H. Peter and Mar, Victoria
- organization
- publishing date
- 2024
- type
- Contribution to journal
- publication status
- in press
- subject
- keywords
- artificial intellgience, melanoma, mobile applications, skin cancer, Software as a Medical Device
- in
- Australasian Journal of Dermatology
- publisher
- Wiley-Blackwell
- external identifiers
-
- pmid:38693690
- scopus:85192180050
- ISSN
- 0004-8380
- DOI
- 10.1111/ajd.14269
- language
- English
- LU publication?
- yes
- id
- db6811c8-0854-41c1-a1be-7752ba8b410f
- date added to LUP
- 2024-05-16 13:02:03
- date last changed
- 2024-05-30 14:53:55
@article{db6811c8-0854-41c1-a1be-7752ba8b410f, abstract = {{<p>In recent years, there has been a surge in the development of AI-based Software as a Medical Device (SaMD), particularly in visual specialties such as dermatology. In Australia, the Therapeutic Goods Administration (TGA) regulates AI-based SaMD to ensure its safe use. Proper labelling of these devices is crucial to ensure that healthcare professionals and the general public understand how to use them and interpret results accurately. However, guidelines for labelling AI-based SaMD in dermatology are lacking, which may result in products failing to provide essential information about algorithm development and performance metrics. This review examines existing labelling guidelines for AI-based SaMD across visual medical specialties, with a specific focus on dermatology. Common recommendations for labelling are identified and applied to currently available dermatology AI-based SaMD mobile applications to determine usage of these labels. Of the 21 AI-based SaMD mobile applications identified, none fully comply with common labelling recommendations. Results highlight the need for standardized labelling guidelines. Ensuring transparency and accessibility of information is essential for the safe integration of AI into health care and preventing potential risks associated with inaccurate clinical decisions.</p>}}, author = {{Oloruntoba, Ayooluwatomiwa and Ingvar, Åsa and Sashindranath, Maithili and Anthony, Ojochonu and Abbott, Lisa and Guitera, Pascale and Caccetta, Tony and Janda, Monika and Soyer, H. Peter and Mar, Victoria}}, issn = {{0004-8380}}, keywords = {{artificial intellgience; melanoma; mobile applications; skin cancer; Software as a Medical Device}}, language = {{eng}}, publisher = {{Wiley-Blackwell}}, series = {{Australasian Journal of Dermatology}}, title = {{Examining labelling guidelines for AI-based software as a medical device : A review and analysis of dermatology mobile applications in Australia}}, url = {{http://dx.doi.org/10.1111/ajd.14269}}, doi = {{10.1111/ajd.14269}}, year = {{2024}}, }