Artificial intelligence (AI)-powered imaging for objective psoriasis severity assessment at home: Feasibility and reliability in a randomized clinical trial

Journal of the American Academy of Dermatology 2026 Open access

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Authors: Mariona Oliver, Monika Molnárová, Menthe Bergmans, Rahul Ranjan, Vasileios Exadaktylos, Tessa Niemeyer van der Kolk, Marieke M.B. Seyger, Leonard Wee, Deepak M.W. Balak, Martijn B. A. van Doorn, Robert Rißmann, Harald Schnidar
+28 more Jannik Rousel, Rob Vreeken, Eva Cuypers, Sylvia van Beugen, Antoinette I. M. van Laarhoven, Boudewijn Lelieveldt, Abdoel El Ghalbzouri, Juul van den Reek, Ellen van den Bogaard, Elke de Jong, Peter van den Broek, Bernd Arents, Ton de Leeuw, Tom Ederveen, Peter Bram ’t Hoen, Annemarie Sluijmers, Bernd Arents, Mieke de Leeuw, Ton de Leeuw, Peter van den Broek, Els van der Pool, Lisanne Wezendonk, Douwe Vellinga, Stephan Weidinger, Sandrine Dubrak, Yang Li, M. van Steensel, Martina Marchetti-Deschmann
DOI: 10.1016/j.jaad.2026.06.047
Cited by: 1
References: 5

Abstract

Artificial intelligence (AI)-powered imaging for objective psoriasis severity assessment at home: Feasibility and reliability in a randomized clinical trial Key Message: Patient-captured smartphone images analyzed by AI, reliably detect and quantify treatment-related changes consistent with physician scoring.

Fields of Study & Subjects

Psoriasis: Treatment and Pathogenesis Spondyloarthritis Studies and Treatments Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Journal of the American Academy of Dermatology
Publisher
Elsevier BV
Volume
95
Issue
4
Pages
1182–1184
Publication date
14 June 2026
Language
EN