This study is to create a self-learning software that can detect acne lesions. Patients take a picture of their face every single day for 3 months with a secure mobile phone and fill out a pre-designed questionnaire. After 3 months, the mobile will be collected back and the pictures will be evaluated by 3 dermatologists. The software is able to learn from the dermatologists' evaluation and -using machine learning- a mechanism that should be able to automatically detect acne to some extent will be established.
Study Type
OBSERVATIONAL
Enrollment
25
Self- learning software that can detect acne lesions from patients who take a picture of their face every single day for 3 months with a secure mobile phone.
Collection of patient reported outcomes and clinical data via a mobile electronic case report form
Department of Dermatology, University Hospital Basel
Basel, Switzerland
Pictures to train the AcneDect software
Collection of pictures to train the AcneDect software to detect change in acne lesions
Time frame: every single day from baseline for 3 months
AcneDect questionnaire regarding acne burden (Visual Analogue Scale (VAS) scale ranging from "Not bad at all" to "Very bad")
Collection of patient reported outcomes via a mobile electronic case report form
Time frame: every single day from baseline for 3 months
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