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

New Methods (1010) Digital Biomarkers and Digital Phenotyping (218) Imaging Informatics (217) Machine Learning (1651) Data Science (297) Artificial Intelligence (1628)

Published on in Vol 26 (2024)

This is a member publication of Charite - Universitaetsmedizin Berlin, Medizinische Bibliothek, Germany

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42904, first published .
Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study

Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study

Validation of 3 Computer-Aided Facial Phenotyping Tools (DeepGestalt, GestaltMatcher, and D-Score): Comparative Diagnostic Accuracy Study

Authors of this article:

Alisa Maria Vittoria Reiter1 Author Orcid Image ;   Jean Tori Pantel1, 2, 3 Author Orcid Image ;   Magdalena Danyel1, 4, 5 Author Orcid Image ;   Denise Horn1 Author Orcid Image ;   Claus-Eric Ott1 Author Orcid Image ;   Martin Atta Mensah1, 6 Author Orcid Image
Article Authors Cited by (4) Tweetations (13) Metrics

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  3. Pascolini G, Didona D, Tarani L. An Artificial Intelligence Approach to the Craniofacial Recapitulation of Crisponi/Cold-Induced Sweating Syndrome 1 (CISS1/CISS) from Newborns to Adolescent Patients. Diagnostics 2025;15(5):521 View

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