Acne Lesions | Acne Detection Software (AcneDect)
Acne Lesions research study
What is the primary objective of this study?
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.
Who is eligible to participate?
Inclusion Criteria: - Acne vulgaris Exclusion Criteria: - Refusal to participate
Which medical condition, disease, disorder, syndrome, illness, or injury is researched?
Interventions can include giving participants drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available or noninvasive approaches such as surveys, education, and interviews.
Other:Self- learning software that can detect acne lesionsSelf- 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.
Other:Patient reported outcomesCollection of patient reported outcomes and clinical data via a mobile electronic case report form
Research studies and clinical trials typically have two or more research arms. An arm is a group of people who receive the same treatment in the study.
Not yet recruiting
Start Date: September 2019
Completed Date: October 2020
Primary Outcome: Collection of pictures to train the AcneDect software
Secondary Outcome: AcneDect questionnaire regarding acne burden (VAS scale ranging from "Not bad at all" to "Very bad")
Study sponsors, principal investigator, and references
Principal Investigator: Alexander A. Navarini, Prof. Dr. MD
Lead Sponsor: University Hospital, Basel, Switzerland