Acne Detection Software (AcneDect)

Terminated

• Conditions: Acne Lesions; Acne Vulgaris

• Registration Number: NCT04060160
• Lead Sponsor: University Hospital, Basel, Switzerland

Brief Summary

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2019-08-15
• Study First Submitted QC: 2019-08-15
• Study First Posted: 2019-08-16
• Study Start: 2020-10-29
• Primary Completion: 2024-09-30
• Study Completion: 2024-09-30
• Status Verified: 2025-01
• Last Update Submitted: 2025-01-13
• Last Update Posted: 2025-01-15

Recruitment & Eligibility

• Status: TERMINATED
• Sex: All
• Target Recruitment: 25

Inclusion Criteria

• Acne vulgaris

Exclusion Criteria

• Refusal to participate

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
Pictures to train the AcneDect software	every single day from baseline for 3 months	Collection of pictures to train the AcneDect software to detect change in acne lesions

Secondary Outcome Measures

Name	Time	Method
AcneDect questionnaire regarding acne burden (Visual Analogue Scale (VAS) scale ranging from "Not bad at all" to "Very bad")	every single day from baseline for 3 months	Collection of patient reported outcomes via a mobile electronic case report form

Trial Locations

Locations (1)

Department of Dermatology, University Hospital Basel; 🇨🇭 Basel, Switzerland