This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2491) Clinical Information and Decision Making (1434) Artificial Intelligence (1421) Machine Learning (1501) Decision Support for Health Professionals (1210) Atopic Eczema (16) Dermatology (47) Innovations in Dermatological Electronic Health Records and Documentation (3) Natural Language Processing (706)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://www.medrxiv.org/content/10.1101/v1, first published .
Patient Phenotyping for Atopic Dermatitis With Transformers and Machine Learning: Algorithm Development and Validation Study

Patient Phenotyping for Atopic Dermatitis With Transformers and Machine Learning: Algorithm Development and Validation Study

Patient Phenotyping for Atopic Dermatitis With Transformers and Machine Learning: Algorithm Development and Validation Study

Authors of this article:

Andrew Wang1 Author Orcid Image ;   Rachel Fulton2 Author Orcid Image ;   Sy Hwang1 Author Orcid Image ;   David J Margolis1 Author Orcid Image ;   Danielle Mowery1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Paganelli A, Spadafora M, Navarrete‐Dechent C, Guida S, Pellacani G, Longo C. Natural language processing in dermatology: A systematic literature review and state of the art. Journal of the European Academy of Dermatology and Venereology 2024;38(12):2225 View