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Acne Detection Software (AcneDect)

NCT04060160 · Status: TERMINATED · Type: OBSERVATIONAL · Enrollment: 25

Last updated 2025-01-15

No results posted yet for this study

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.

Conditions

  • Acne Lesions
  • Acne Vulgaris

Interventions

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.

OTHER

Patient reported outcomes

Collection of patient reported outcomes and clinical data via a mobile electronic case report form

Sponsors & Collaborators

  • University Hospital, Basel, Switzerland

    lead OTHER

Principal Investigators

  • Alexander A. Navarini, Prof. Dr. MD · Dermatologische Klinik; Universitätshospital Basel

Eligibility

Min Age
10 Years
Max Age
35 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-10-29
Primary Completion
2024-09-30
Completion
2024-09-30

Countries

  • Switzerland

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04060160 on ClinicalTrials.gov