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Acne Detection Software (AcneDect) (AcneDect)

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ClinicalTrials.gov Identifier: NCT04060160
Recruitment Status : Recruiting
First Posted : August 16, 2019
Last Update Posted : April 12, 2022
Sponsor:
Information provided by (Responsible Party):
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.

Condition or disease Intervention/treatment
Acne Lesions Acne Vulgaris Other: Self- learning software that can detect acne lesions Other: Patient reported outcomes

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Study Type : Observational
Estimated Enrollment : 40 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Acne Detection Software (AcneDect); AcneDect: a Software to Detect Acne Lesions
Actual Study Start Date : October 29, 2020
Estimated Primary Completion Date : December 2022
Estimated Study Completion Date : December 2022

Resource links provided by the National Library of Medicine

MedlinePlus related topics: Acne


Intervention Details:
  • 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


Primary Outcome Measures :
  1. Pictures to train the AcneDect software [ Time Frame: 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 :
  1. AcneDect questionnaire regarding acne burden (Visual Analogue Scale (VAS) scale ranging from "Not bad at all" to "Very bad") [ Time Frame: every single day from baseline for 3 months ]
    Collection of patient reported outcomes via a mobile electronic case report form



Information from the National Library of Medicine

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Ages Eligible for Study:   10 Years to 35 Years   (Child, Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Probability Sample
Study Population
Patients within the consultation service of Dermatologische Klinik, Universitätsspital Basel, that meet the inclusion criteria
Criteria

Inclusion Criteria:

  • Acne vulgaris

Exclusion Criteria:

  • Refusal to participate

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT04060160


Contacts
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Contact: Alexander A. Navarini, Prof. Dr. MD +41 61 265 25 25 alexander.navarini@usb.ch
Contact: Simon Müller, Dr. med +41 61 265 25 25 simon.mueller@usb.ch

Locations
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Switzerland
Department of Dermatology, University Hospital Basel Recruiting
Basel, Switzerland, 4031
Contact: Alexander A. Navarini, Prof. Dr. MD    +41 61 265 25 25    alexander.navarini@usb.ch   
Contact: Simon Müller, Dr. med    0041 61 328 6964    simon.mueller@usb.ch   
Principal Investigator: Alexander Navarini, Prof. Dr. MD         
Sub-Investigator: Dennis Arnold, Pract.med         
Sub-Investigator: Simon Müller, Dr. med         
Sponsors and Collaborators
University Hospital, Basel, Switzerland
Investigators
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Principal Investigator: Alexander A. Navarini, Prof. Dr. MD Dermatologische Klinik; Universitätshospital Basel
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Responsible Party: University Hospital, Basel, Switzerland
ClinicalTrials.gov Identifier: NCT04060160    
Other Study ID Numbers: 2018-00702; sp19Navarini
First Posted: August 16, 2019    Key Record Dates
Last Update Posted: April 12, 2022
Last Verified: April 2022

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No
Keywords provided by University Hospital, Basel, Switzerland:
machine learning
self-learning software
image-detecting software
Additional relevant MeSH terms:
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Acne Vulgaris
Acneiform Eruptions
Skin Diseases
Sebaceous Gland Diseases