A Skin Image Reference Tool to Aid Healthcare Providers' Diagnosis

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

400 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-09-15

Study Completion Date

2027-12-31

Brief Summary

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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

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Detailed Description

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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.

Conditions

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Dermatologic Disease

Study Design

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Observational Model Type

OTHER

Study Time Perspective

PROSPECTIVE

Study Groups

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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.

No interventions assigned to this group

Eligibility Criteria

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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).

Minimum Eligible Age

10 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No