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Examining labelling guidelines for AI-based software as a medical device: A review and analysis of dermatology mobile applications in Australia.
Oloruntoba, Ayooluwatomiwa; Ingvar, Åsa; Sashindranath, Maithili; Anthony, Ojochonu; Abbott, Lisa; Guitera, Pascale; Caccetta, Tony; Janda, Monika; Soyer, H Peter; Mar, Victoria.
Afiliação
  • Oloruntoba A; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Ingvar Å; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Sashindranath M; Victorian Melanoma Service, Alfred Health, Melbourne, Victoria, Australia.
  • Anthony O; Department of Dermatology, Skåne University Hospital, Lund University, Lund, Sweden.
  • Abbott L; Department of Clinical Sciences, Skåne University Hospital, Lund University, Lund, Sweden.
  • Guitera P; School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Caccetta T; Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria, Australia.
  • Janda M; Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
  • Soyer HP; Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
  • Mar V; Sydney Melanoma Diagnostic Centre, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia.
Australas J Dermatol ; 65(5): 409-422, 2024 Aug.
Article em En | MEDLINE | ID: mdl-38693690
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 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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rotulagem de Produtos / Dermatologia / Aplicativos Móveis Limite: Humans País/Região como assunto: Oceania Idioma: En Revista: Australas J Dermatol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Rotulagem de Produtos / Dermatologia / Aplicativos Móveis Limite: Humans País/Região como assunto: Oceania Idioma: En Revista: Australas J Dermatol Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Austrália