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RecruitingNCT07033169Updated Sep 28, 2026

A Skin Image Reference Tool to Aid Healthcare Providers' Diagnosis

An observational study in Dermatologic Disease, sponsored by Wake Forest University Health Sciences. Recruiting at 1 site in United States. Open to participants aged 10 Years and older. Per ClinicalTrials.gov, last updated 2026-09-28.

Sponsored by Wake Forest University Health Sciences · Observational

Study type
Observational
Model
Other
Time perspective
Prospective
Enrollment
400
Ages
10 Years and older
Sex
All
01

Study summary

Consented patients will have three images taken of their dermatologic conditions within the Belle.ai software. These images will be uploaded and saved within the Belle software system where a single AI-generated differential list will be generated based on the three photos. All photos uploaded will be de-identified. The software will not have any unique identifiers of participants saved in the system. The photos will be named based on participant enrollment numbers or unique code numbers and no unique identifiers will be attached to the photos. There will be no data collection form necessary for this study

Read the detailed description

Belle.ai provides a differential diagnosis from more than 2,000 different skin conditions leveraging a database trained on over 500,000 images. The image referencing technology deploys deep learning to analyze an uploaded clinical image and then matches its geometric pattern characteristics to Belle.ai's database of images to provide reference differentials. The purpose is to determine the validity of the Belle.ai software in diagnosing common dermatologic diseases across a range of skin tones.

Consented patients will have three images taken of their dermatologic disease within the Belle.ai software. These images will be uploaded and saved within the Belle system where a single AI-generated differential list will be generated based on the three photos. The study coordinator will review uploaded patient "cases" and assign the cases for review and adjudication to designated Dermatologic Review Committee (DRC) members within the Belle web portal. Successful validation will require >80% concordance between Belle.ai's primary working diagnosis (#1 on the differential) and our dermatology experts. A team of dermatology experts will then secondarily assess the concordance among the remaining diagnoses.

02

Conditions studied

  • Dermatologic Disease

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Keywords

  • artificial intelligence
  • skin diseases
  • dermatology
03

Who can participate

Ages eligible
10 Years and older
Sexes eligible
All
Sampling method
Non-probability sample

Study population

Up to 400 participants will be recruited for this study

Inclusion criteria

  • Patient must present to an Advocate Health dermatology clinic
  • Patient must have the ability and willingness to provide informed consent and comply with study procedures and visits
  • Participant dermatologists must have access to the required technology (e.g., smartphone with internet access) and be capable of using it for the required image capture

Exclusion criteria

Exclusion Criteria:

  • Patients who are unable to comply with study procedures due to physical or mental health limitations (as assessed by study coordinator)
  • Pediatric, adolescent, and teen patients who present with dermatological conditions on their genitalia will not be included in the study (in support of patient privacy concerns).
04

Study design

Observational model
Other
Time perspective
Prospective
Enrollment
400 participants (estimated)
Patient registry
No

Groups and cohorts

  • Patient at Advocate Health dermatology clinic

    The study, subject recruitment, and analysis will be conducted within the Advocate Health system at Atrium Health Wake Forest Baptist (AHWFB) in Winston-Salem, NC. Recruiters for this study include Advocate Health dermatology attendings, fellows, and staff, who will capture images of patients presenting to Wake Forest Dermatology Clinics in Winston-Salem, NC.

05

What researchers measure

Primary outcomes

  1. concordance of Belle.ai diagnoses with physician diagnoses.

    The study coordinator will review uploaded patient "cases" and assign them for review and adjudication to designated Dermatologic Review Committee (DRC) members within the Belle web portal. The DRC will be comprised of 1-2 Advocate Health board-certified dermatologists from each of the Winston, Charlotte, and Midwest dermatology practices.

    Time frame: Day 1

06

Study locations

1 of 1 sites recruiting
  • Wake Forest University Health Sciences Department of Dermatology
    Winston-Salem, North Carolina 27157, United States
    Recruiting
07

References and documents

Individual participant data

Plan to share: Undecided — The images will be uploaded and saved within the Belle system where a single AI-generated differential list will be generated based on the three photos. The study coordinator will review uploaded patient "cases" and assign the cases for review and adjudication to designated Dermatologic Review Committee (DRC) members within the Belle web portal.

No publications or documents are linked to this record.

08

Registry details

Key details

Study ID
NCT07033169
Lead sponsor
Wake Forest University Health Sciences
Collaborators
BelleTorus Corporation
Responsible party
Sponsor
First posted
Jun 24, 2025
Start date
Sep 15, 2025
Primary completion
Sep 2027 (estimated)
Completion
Dec 2027 (estimated)
Last update
Sep 28, 2026

Study contacts

Irma M Richardson, MHA
Contact
irma.richardson@advocatehealth.org
336-716-2903
Lindsay C Strowd, MD
principal investigator · Wake Forest University Health Sciences

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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