Artificial Intelligence Patient App for RDEB SCCs
Public ClinicalTrials.gov record NCT05843994. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.
Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.
Official title
Developing a Novel Artificial Intelligence Patient App to Recognize Squamous Cell Carcinoma (SCCs) in Recessive Dystrophic Epidermolysis Bullosa (RDEB): Image Collection
Brief summary
Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.
In this study, an artificial intelligence model to detect squamous cell carcinomas (SCC) on photos of recessive dystrophic epidermolysis bullosa (RDEB) skin is developed. The ultimate goal is to integrate this model into an app for patients and physicians, to help detect SCCs in RDEB early. SCCs which rapidly metastasize are the main cause of death in adults with RDEB. The earlier an SCC is recognized, the easier it can be removed and the better the outcome. AI leverages computer science to perform tasks that typically require human intelligence and has recently been used to identify skin cancers based on images. We are currently developing an AI approach for early detection of SCC and distinction of malignancy from chronic wounds and other RDEB skin findings. The aim is to create a web application for patients with RDEB to upload images of their skin and get an output as to SCC present/ no SCC. This will be especially valuable for patients with difficult access to medical expertise and those who are hesitant to allow full skin examination at each visit, often because of fear of biopsies. Thus, this project will directly benefit patients by allowing early recognition of SCCs and will empower patients and their families by providing a home use tool. So far, the study team has mainly used professional images (photographs taken in hospital settings by physicians, nurses, and clinical photographers) of both SCCs in RDEB and images of RDEB skin without SCC to develop and train the AI model. The images that are expected in a real-life setting will mostly be pictures taken by patients or family members with their phones or digital cameras. These images have different properties regarding resolution, focus, lighting, and backgrounds. Incorporating such images will be crucial in the upcoming phases of model development-testing and validation-for the web application be a success for patients.
Study identification
- NCT ID
- NCT05843994
- Recruitment status
- Active, not recruiting
- Study type
- Observational
- Phase
- Not listed
- Enrollment
- 20 participants
Conditions and interventions
Conditions
Eligibility (public fields only)
- Age range
- 12 Years and older
- Sex
- All
- Healthy volunteers
- Healthy volunteers not accepted
This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.
Study timeline
- Start date
- Jan 29, 2023
- Primary completion
- Nov 29, 2028
- Completion
- Nov 29, 2028
- Last update posted
- Feb 2, 2026
2023 – 2028
United States locations
- U.S. sites
- 1
- U.S. states
- 1
- U.S. cities
- 1
| Facility | City | State | ZIP | Site status |
|---|---|---|---|---|
| Department of Dermatology, Northwestern University Feinberg School of Medicine and Lurie Children's Hospital | Chicago | Illinois | 60611 | — |
Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.
About this trial record page
- What this page shows
- Public field values for ClinicalTrials.gov record NCT05843994, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
- What this page does not do
- No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
- Where the data comes from
- Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
- Last refresh
- Last update posted Feb 2, 2026 · Synced Sep 10, 2026
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Open the official record
The complete protocol, eligibility criteria, and contact information for NCT05843994 live on ClinicalTrials.gov.