Skin image reference tool to help doctors diagnose skin conditions
Official title: A Skin Image Reference Tool to Aid Healthcare Providers' Diagnosis of Commonly Encountered Dermatologic Diseases
Run by Wake Forest University Health Sciences · NCT07033169 · Data updated 2026-11-12
This project will test whether Belle.ai can use three de-identified photos to help dermatologists at an Advocate Health clinic pick the right diagnosis for common skin conditions.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 10 Years and up |
| Sex | All |
| Enrollment | 400 (estimated) |
| Sponsor | Wake Forest University Health Sciences Academic / other |
| Locations | 1 site (Winston-Salem, North Carolina) |
| Status | Recruiting |
| Started | September 15, 2025 |
| Main results expected | September 2027 |
| Study ends | December 2027 |
| Registry record updated | September 28, 2026 |
| Trial ID | NCT07033169 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Patients who present to an Advocate Health dermatology clinic with visible skin conditions, can give informed consent, and whose clinicians can capture and upload smartphone images are the intended participants.
✕Probably not a fit
Patients who cannot comply with image capture or consent requirements, and pediatric patients with genital lesions (excluded for privacy), are unlikely to benefit from participation.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Consented patients will have three clinical photos uploaded into the Belle.ai system, which uses deep learning trained on over 500,000 images to generate a differential from more than 2,000 skin conditions. All photos are de-identified and labeled only with study codes, and no other patient data are collected. A Dermatologic Review Committee of experts will review and adjudicate cases within the Belle web portal to compare the AI's primary working diagnosis to expert opinion. Success is defined as greater than 80% concordance between Belle.ai's top diagnosis and the dermatology experts, with secondary review of the remaining differential.
Why it matters
Potential benefit: If successful, the tool could speed and standardize dermatology diagnoses, improving timely treatment and access to care.
How similar studies have gone: Other AI-based dermatology image tools have shown promising results for some common conditions, but external validation and consistent performance across diverse skin tones remain variable.
Who can join: the full rules
Show full inclusion / exclusion criteria
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: * 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).
Where it's running
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Wake Forest University Health Sciences Department of Dermatology
Winston-Salem, North Carolina, United States Recruiting
Study contacts
- Principal investigator: Lindsay C Strowd, MD — Wake Forest University Health Sciences
- Study coordinator: Irma M Richardson, MHA
- Email: irma.richardson@advocatehealth.org
- Phone: 336-716-2903
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.