دورية أكاديمية
Artificial intelligence in skin cancer smartphone applications.
العنوان: | Artificial intelligence in skin cancer smartphone applications. |
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عنوان ترانسليتريتد: | Künstliche Intelligenz in Hautkrebs-Smartphone-Apps. |
المؤلفون: | Sangers TE; Leiden University Medical Center, Albinusdreef 2, 2333 ZD, Leiden, The Netherlands. t.e.sangers@lumc.nl. |
المصدر: | Dermatologie (Heidelberg, Germany) [Dermatologie (Heidelb)] 2024 Apr; Vol. 75 (4), pp. 344-346. Date of Electronic Publication: 2023 Dec 29. |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Springer Medizin Country of Publication: Germany NLM ID: 9918384885206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2731-7013 (Electronic) Linking ISSN: 27317005 NLM ISO Abbreviation: Dermatologie (Heidelb) Subsets: MEDLINE |
أسماء مطبوعة: | Original Publication: [Heidelberg, Germany] : Springer Medizin, [2022]- |
مواضيع طبية MeSH: | Mobile Applications* , Skin Neoplasms*/diagnosis, Humans ; Artificial Intelligence ; Smartphone |
References: | Statista Number of smartphone users worldwide. https://www.statista.com/statistics/330695/number-of-smartphone-users-worldwide/ . Accessed 26-11-2023,. de Carvalho TM, Noels E, Wakkee M, Udrea A, Nijsten T (2019) Development of smartphone apps for skin cancer risk assessment: progress and promise. JMIR Dermatol 2(1):e13376. https://doi.org/10.2196/13376. (PMID: 10.2196/13376) Esteva A, Kuprel B, Novoa RA et al (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542(7639):115–118. https://doi.org/10.1038/nature21056. (PMID: 10.1038/nature21056281174458382232) Freeman K, Dinnes J, Chuchu N et al (2020) Algorithm based smartphone apps to assess risk of skin cancer in adults: systematic review of diagnostic accuracy studies. BMJ 368:m127. https://doi.org/10.1136/bmj.m127. (PMID: 10.1136/bmj.m127320416937190019) Matin RN, Dinnes J (2021) AI-based smartphone apps for risk assessment of skin cancer need more evaluation and better regulation. Br J Cancer 124(11):1749–1750. https://doi.org/10.1038/s41416-021-01302-3. (PMID: 10.1038/s41416-021-01302-3337421488144419) Sangers TE, Kittler H, Blum A et al (2023) Position statement of the EADV Artificial Intelligence (AI) task force on AI-assisted smartphone apps and web-based services for skin disease. Acad Dermatol Venereol. https://doi.org/10.1111/jdv.19521. (PMID: 10.1111/jdv.19521) Sangers T, Reeder S, van der Vet S et al (2022) Validation of a market-approved artificial intelligence mobile health app for skin cancer screening: a prospective multicenter diagnostic accuracy study. Dermatology 238(4):649–656. https://doi.org/10.1159/000520474. (PMID: 10.1159/00052047435124665) Smak Gregoor AM, Sangers TE, Bakker LJ et al (2023) An artificial intelligence based app for skin cancer detection evaluated in a population based setting. Npj Digit Med 6(1):90. https://doi.org/10.1038/s41746-023-00831-w. (PMID: 10.1038/s41746-023-00831-w3721046610199884) Sangers TE, Wakkee M, Kramer-Noels EC, Nijsten T, Lugtenberg M (2021) Views on mobile health apps for skin cancer screening in the general population: an in-depth qualitative exploration of perceived barriers and facilitators. Br J Dermatol 185(5):961–969. https://doi.org/10.1111/bjd.20441. (PMID: 10.1111/bjd.20441339599459291092) |
تواريخ الأحداث: | Date Created: 20231229 Date Completed: 20240327 Latest Revision: 20240327 |
رمز التحديث: | 20240327 |
DOI: | 10.1007/s00105-023-05289-1 |
PMID: | 38156999 |
قاعدة البيانات: | MEDLINE |
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