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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT04060160
Other study ID # 2018-00702; sp19Navarini
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date October 29, 2020
Est. completion date December 2022

Study information

Verified date April 2022
Source University Hospital, Basel, Switzerland
Contact Alexander A. Navarini, Prof. Dr. MD
Phone +41 61 265 25 25
Email alexander.navarini@usb.ch
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial 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.


Recruitment information / eligibility

Status Recruiting
Enrollment 40
Est. completion date December 2022
Est. primary completion date December 2022
Accepts healthy volunteers No
Gender All
Age group 10 Years to 35 Years
Eligibility Inclusion Criteria: - Acne vulgaris Exclusion Criteria: - Refusal to participate

Study Design


Related Conditions & MeSH terms


Intervention

Other:
Self- learning software that can detect acne lesions
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.
Patient reported outcomes
Collection of patient reported outcomes and clinical data via a mobile electronic case report form

Locations

Country Name City State
Switzerland Department of Dermatology, University Hospital Basel Basel

Sponsors (1)

Lead Sponsor Collaborator
University Hospital, Basel, Switzerland

Country where clinical trial is conducted

Switzerland, 

Outcome

Type Measure Description Time frame Safety issue
Primary Pictures to train the AcneDect software Collection of pictures to train the AcneDect software to detect change in acne lesions every single day from baseline for 3 months
Secondary 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 every single day from baseline for 3 months
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