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Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study

BACKGROUND: Artificial intelligence (AI)-based mobile phone apps (mHealth) have the potential to streamline care for suspicious skin lesions in primary care. This study aims to investigate the conditions and feasibility of a study that incorporates an AI-based app in primary care and evaluates its p...

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Autores principales: Smak Gregoor, Anna M., Sangers, Tobias E., Eekhof, Just AH., Howe, Sydney, Revelman, Jeroen, Litjens, Romy JM., Sarac, Mohammed, Bindels, Patrick JE., Bonten, Tobias, Wehrens, Rik, Wakkee, Marlies
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10227364/
https://www.ncbi.nlm.nih.gov/pubmed/37261324
http://dx.doi.org/10.1016/j.eclinm.2023.102019
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author Smak Gregoor, Anna M.
Sangers, Tobias E.
Eekhof, Just AH.
Howe, Sydney
Revelman, Jeroen
Litjens, Romy JM.
Sarac, Mohammed
Bindels, Patrick JE.
Bonten, Tobias
Wehrens, Rik
Wakkee, Marlies
author_facet Smak Gregoor, Anna M.
Sangers, Tobias E.
Eekhof, Just AH.
Howe, Sydney
Revelman, Jeroen
Litjens, Romy JM.
Sarac, Mohammed
Bindels, Patrick JE.
Bonten, Tobias
Wehrens, Rik
Wakkee, Marlies
author_sort Smak Gregoor, Anna M.
collection PubMed
description BACKGROUND: Artificial intelligence (AI)-based mobile phone apps (mHealth) have the potential to streamline care for suspicious skin lesions in primary care. This study aims to investigate the conditions and feasibility of a study that incorporates an AI-based app in primary care and evaluates its potential impact. METHODS: We conducted a pilot feasibility study from November 22nd, 2021 to June 9th, 2022 with a mixed-methods design on implementation of an AI-based mHealth app for skin cancer detection in three primary care practices in the Netherlands (Rotterdam, Leiden and Katwijk). The primary outcome was the inclusion and successful participation rate of patients and general practitioners (GPs). Secondary outcomes were the reasons, facilitators and barriers for successful participation and the potential impact in both pathways for future sample size calculations. Patients were offered use of an AI-based mHealth app before consulting their GP. GPs assessed the patients blinded and then unblinded to the app. Qualitative data included observations and audio-diaries from patients and GPs and focus-groups and interviews with GPs and GP assistants. FINDINGS: Fifty patients were included with a median age of 52 years (IQR 33.5–60.3), 64% were female, and 90% had a light skin type. The average patient inclusion rate was 4–6 per GP practice per month and 84% (n = 42) successfully participated. Similarly, in 90% (n = 45 patients) the GPs also successfully completed the study. GPs never changed their working diagnosis, but did change their treatment plan (n = 5) based on the app's assessments. Notably, 54% of patients with a benign skin lesion and low risk rating, indicated that they would be reassured and cancel their GP visit with these results (p < 0.001). INTERPRETATION: Our findings suggest that studying implementation of an AI-based mHealth app for detection of skin cancer in the hands of patients or as a diagnostic tool used by GPs in primary care appears feasible. Preliminary results indicate potential to further investigate both intended use settings. FUNDING: SkinVision B.V.
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spelling pubmed-102273642023-05-31 Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study Smak Gregoor, Anna M. Sangers, Tobias E. Eekhof, Just AH. Howe, Sydney Revelman, Jeroen Litjens, Romy JM. Sarac, Mohammed Bindels, Patrick JE. Bonten, Tobias Wehrens, Rik Wakkee, Marlies eClinicalMedicine Articles BACKGROUND: Artificial intelligence (AI)-based mobile phone apps (mHealth) have the potential to streamline care for suspicious skin lesions in primary care. This study aims to investigate the conditions and feasibility of a study that incorporates an AI-based app in primary care and evaluates its potential impact. METHODS: We conducted a pilot feasibility study from November 22nd, 2021 to June 9th, 2022 with a mixed-methods design on implementation of an AI-based mHealth app for skin cancer detection in three primary care practices in the Netherlands (Rotterdam, Leiden and Katwijk). The primary outcome was the inclusion and successful participation rate of patients and general practitioners (GPs). Secondary outcomes were the reasons, facilitators and barriers for successful participation and the potential impact in both pathways for future sample size calculations. Patients were offered use of an AI-based mHealth app before consulting their GP. GPs assessed the patients blinded and then unblinded to the app. Qualitative data included observations and audio-diaries from patients and GPs and focus-groups and interviews with GPs and GP assistants. FINDINGS: Fifty patients were included with a median age of 52 years (IQR 33.5–60.3), 64% were female, and 90% had a light skin type. The average patient inclusion rate was 4–6 per GP practice per month and 84% (n = 42) successfully participated. Similarly, in 90% (n = 45 patients) the GPs also successfully completed the study. GPs never changed their working diagnosis, but did change their treatment plan (n = 5) based on the app's assessments. Notably, 54% of patients with a benign skin lesion and low risk rating, indicated that they would be reassured and cancel their GP visit with these results (p < 0.001). INTERPRETATION: Our findings suggest that studying implementation of an AI-based mHealth app for detection of skin cancer in the hands of patients or as a diagnostic tool used by GPs in primary care appears feasible. Preliminary results indicate potential to further investigate both intended use settings. FUNDING: SkinVision B.V. Elsevier 2023-05-25 /pmc/articles/PMC10227364/ /pubmed/37261324 http://dx.doi.org/10.1016/j.eclinm.2023.102019 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Smak Gregoor, Anna M.
Sangers, Tobias E.
Eekhof, Just AH.
Howe, Sydney
Revelman, Jeroen
Litjens, Romy JM.
Sarac, Mohammed
Bindels, Patrick JE.
Bonten, Tobias
Wehrens, Rik
Wakkee, Marlies
Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title_full Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title_fullStr Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title_full_unstemmed Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title_short Artificial intelligence in mobile health for skin cancer diagnostics at home (AIM HIGH): a pilot feasibility study
title_sort artificial intelligence in mobile health for skin cancer diagnostics at home (aim high): a pilot feasibility study
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10227364/
https://www.ncbi.nlm.nih.gov/pubmed/37261324
http://dx.doi.org/10.1016/j.eclinm.2023.102019
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