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

Mobile Health (mhealth) (2939) Digital Health, Telehealth and e-Innovation in Clinical Settings (401) Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Machine Learning (1465) mHealth for Health Administration (144) Adoption and Change Management of eHealth Systems (712)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50886, first published .
Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study

Authors of this article:

Igor Bibi1 Author Orcid Image ;   Daniel Schaffert1 Author Orcid Image ;   Mara Blauth1 Author Orcid Image ;   Christian Lull1 Author Orcid Image ;   Jan Alwin von Ahnen1 Author Orcid Image ;   Georg Gross2 Author Orcid Image ;   Wanja Alexander Weigandt1 Author Orcid Image ;   Johannes Knitza3 Author Orcid Image ;   Sebastian Kuhn3 Author Orcid Image ;   Johannes Benecke1 Author Orcid Image ;   Jan Leipe2 Author Orcid Image ;   Astrid Schmieder4 Author Orcid Image ;   Victor Olsavszky1 Author Orcid Image
Article Authors Cited by (1) Tweetations (7) Metrics

Journals

  1. Schaffert D, Bibi I, Blauth M, Lull C, von Ahnen J, Gross G, Schulze-Hagen T, Knitza J, Kuhn S, Benecke J, Schmieder A, Leipe J, Olsavszky V. Using Automated Machine Learning to Predict Necessary Upcoming Therapy Changes in Patients With Psoriasis Vulgaris and Psoriatic Arthritis and Uncover New Influences on Disease Progression: Retrospective Study. JMIR Formative Research 2024;8:e55855 View