A New TADA-inspired Decision Algorithm for Training Primary Care Practitioners in Dermoscopy

E. Harkemanne,L. Thomas,R. Braun,M. Baeck,I. Tromme

JOURNAL OF THE EUROPEAN ACADEMY OF DERMATOLOGY AND VENEREOLOGY（2023）

Clin Univ St Luc

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Journal of the European Academy of Dermatology and VenereologyVolume 37, Issue 11 p. e1295-e1297 LETTER TO THE EDITOR A new TADA-inspired decision algorithm for training primary care practitioners in dermoscopy E. Harkemanne, Corresponding Author E. Harkemanne [email protected] orcid.org/0000-0001-9936-9868 Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium Institute of Experimental and Clinical Research (IREC), UCLouvain, Brussels, Belgium King Albert II Cancer and Hematology Institute, Cliniques Universitaires Saint-Luc, Brussels, Belgium Correspondence E. Harkemanne, Department of Dermatology, Cliniques Universitaires Saint-Luc, Avenue Hippocrate, 10, Brussels B-1200, Belgium. Email: [email protected]Search for more papers by this authorL. Thomas, L. Thomas orcid.org/0000-0003-1995-2434 Dermatology Department, Lyon Cancer Research Center INSERM, Université Lyon 1, Centre Hospitalier Lyon Sud, Pierre-Bénite, FranceSearch for more papers by this authorR. Braun, R. Braun Dermatology Department, University Hospital Zürich, Zürich, SwitzerlandSearch for more papers by this authorM. Baeck, M. Baeck orcid.org/0000-0003-0499-7939 Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium Institute of Experimental and Clinical Research (IREC), UCLouvain, Brussels, BelgiumSearch for more papers by this authorI. Tromme, I. Tromme Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium King Albert II Cancer and Hematology Institute, Cliniques Universitaires Saint-Luc, Brussels, BelgiumSearch for more papers by this author E. Harkemanne, Corresponding Author E. Harkemanne [email protected] orcid.org/0000-0001-9936-9868 Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium Institute of Experimental and Clinical Research (IREC), UCLouvain, Brussels, Belgium King Albert II Cancer and Hematology Institute, Cliniques Universitaires Saint-Luc, Brussels, Belgium Correspondence E. Harkemanne, Department of Dermatology, Cliniques Universitaires Saint-Luc, Avenue Hippocrate, 10, Brussels B-1200, Belgium. Email: [email protected]Search for more papers by this authorL. Thomas, L. Thomas orcid.org/0000-0003-1995-2434 Dermatology Department, Lyon Cancer Research Center INSERM, Université Lyon 1, Centre Hospitalier Lyon Sud, Pierre-Bénite, FranceSearch for more papers by this authorR. Braun, R. Braun Dermatology Department, University Hospital Zürich, Zürich, SwitzerlandSearch for more papers by this authorM. Baeck, M. Baeck orcid.org/0000-0003-0499-7939 Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium Institute of Experimental and Clinical Research (IREC), UCLouvain, Brussels, BelgiumSearch for more papers by this authorI. Tromme, I. Tromme Dermatology Department, Cliniques Universitaires Saint-Luc, Brussels, Belgium King Albert II Cancer and Hematology Institute, Cliniques Universitaires Saint-Luc, Brussels, BelgiumSearch for more papers by this author First published: 16 June 2023 https://doi.org/10.1111/jdv.19277Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Open Research DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES 1Gonna N, Tran T, Bassett RL, Farris DP, Nelson KC. Sensitivity and specificity for skin cancer diagnosis in primary care providers: a systematic literature review and meta-analysis of educational interventions and diagnostic algorithms. J Cancer Educ. 2022; 37(5): 1563–72. https://doi.org/10.1007/s13187-022-02194-4 10.1007/s13187-022-02194-4 PubMedWeb of Science®Google Scholar 2Argenziano G, Puig S, Zalaudek I, Sera F, Corona R, Alsina M, et al. Dermoscopy improves accuracy of primary care physicians to triage lesions suggestive of skin cancer. J Clin Oncol. 2006; 24(12): 1877–82. https://doi.org/10.1200/JCO.2005.05.0864 10.1200/JCO.2005.05.0864 PubMedWeb of Science®Google Scholar 3Jones OT, Jurascheck LC, van Melle MA, Hickman S, Burrows NP, Hall PN, et al. Dermoscopy for melanoma detection and triage in primary care: a systematic review. BMJ Open. 2019; 9(8):e027529. https://doi.org/10.1136/bmjopen-2018-027529 10.1136/bmjopen-2018-027529 CASPubMedWeb of Science®Google Scholar 4Harkemanne E, Baeck M, Tromme I. Training general practitioners in melanoma diagnosis: a scoping review of the literature. BMJ Open. 2021; 11(3):e043926. https://doi.org/10.1136/bmjopen-2020-043926 10.1136/bmjopen-2020-043926 PubMedWeb of Science®Google Scholar 5Harkemanne E, Duyver C, Leconte S, Sawadogo K, Baeck M, Tromme I. Short- and long-term evaluation of general Practitioners' competences after a training in melanoma diagnosis: refresher training sessions may Be needed. J Cancer Educ. 2022; 37: 1928–41. https://doi.org/10.1007/s13187-021-02063-6 10.1007/s13187-021-02063-6 PubMedWeb of Science®Google Scholar 6Harkemanne E, Legrand C, Sawadogo K, van Maanen A, Vossaert K, Argenziano G, et al. Evaluation of primary care physicians' competence in selective skin tumor triage after short versus long dermoscopy training a randomized non-inferiority trial. J Eur Acad Dermatol Venereol. 2023; 37: 1595–1605. https://doi.org/10.1111/jdv.19087 10.1111/jdv.19087 Web of Science®Google Scholar 7Jaimes N, Marghoob AA. Triage amalgamated Dermoscopic algorithm. J Am Acad Dermatol. 2020; 82(6): 1551–2. https://doi.org/10.1016/j.jaad.2020.01.079 10.1016/j.jaad.2020.01.079 PubMedWeb of Science®Google Scholar Volume37, Issue11Special Issue:International statement for diagnosis and management of VitiligoNovember 2023Pages e1295-e1297 ReferencesRelatedInformation

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Quality of Care Data,Dermoscopy

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Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

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