AI-Driven Early Detection of Skin Cancer
Skin Cancer
2 other identifiers
observational
100
1 country
1
Brief Summary
This study evaluates the feasibility and accuracy of an AI-powered mobile platform (NuvanaDx) for early detection of skin cancer, including melanoma, using smartphone-based imaging. The platform is designed to improve access to early diagnosis, reduce waiting times, and support triage into appropriate care pathways.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P50-P75 for all trials
Started Oct 2025
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
August 20, 2025
CompletedFirst Posted
Study publicly available on registry
August 27, 2025
CompletedStudy Start
First participant enrolled
October 1, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
January 1, 2026
CompletedSeptember 26, 2025
September 1, 2025
2 months
August 20, 2025
September 25, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Diagnostic Accuracy of AI tool compared with dermatologist-confirmed diagnosis
Diagnostic Accuracy of AI tool compared with dermatologist-confirmed diagnosis Time Frame: Up to 12 months Measure: Sensitivity, specificity, and predictive values
Time Frame: Up to 12 months
Study Arms (1)
Participants with suspicious skin lesions undergoing AI-based image analysis and dermatologist confi
Interventions
Smartphone-based AI skin lesion analysis (NuvanaDx platform).
Eligibility Criteria
Study Population Description: Individuals undergoing dermatology evaluation in UK clinics, supplemented by retrospective anonymized image datasets.
You may qualify if:
- Adults (≥18 years) presenting with skin lesions suspicious for malignancy.
- Ability to provide informed consent.
You may not qualify if:
- Inability to provide informed consent.
- Poor-quality images unsuitable for AI analysis.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Nuvana Healthcare Ltd
London, United Kingdom
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- STUDY CHAIR
Aryan Chaudhary,
Scientific Advisor / Co-Founder, Nuvana Healthcare
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- ECOLOGIC OR COMMUNITY
- Time Perspective
- PROSPECTIVE
- Target Duration
- 50 Months
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
August 20, 2025
First Posted
August 27, 2025
Study Start
October 1, 2025
Primary Completion
December 1, 2025
Study Completion
January 1, 2026
Last Updated
September 26, 2025
Record last verified: 2025-09
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ICF, CSR, ANALYTIC CODE
- Time Frame
- De-identified IPD and supporting information will be available beginning 6 months after study completion (anticipated June 2027). Data will remain available for at least 5 years (until December 2032), after which access will be reviewed and may be extended based on scientific demand.
- Access Criteria
- Access will be granted to qualified researchers affiliated with academic institutions, non-profit organizations, or healthcare systems, upon submission of a research proposal that aligns with the study's objectives. Proposals will be reviewed by Nuvana Healthcare's Scientific Advisory Board. Data will be shared under a data use agreement (DUA) to ensure confidentiality and compliance with ethical standards. Access will be provided through a secure, password-protected platform, with no download of raw datasets permitted unless explicitly approved.
Individual Participant Data (IPD) that underlie the results of this study will be shared after de-identification. This will include anonymized image datasets of skin lesions (with corresponding dermatology-confirmed diagnoses), demographic variables (age, sex), and relevant clinical outcomes. No personally identifiable information (PII) will be shared. Data will be made available for the purpose of secondary analysis, validation studies, and meta-analyses in the field of dermatology, oncology, and digital health.