Skin Cancer Melanoma
Conditions
Keywords
Skin Cancer, Melanoma, Early Detection, Artificial Intelligence, Dermatology, Digital Health
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.
Detailed description
The study will collect retrospective and prospective anonymized skin lesion images and metadata to validate the AI algorithm against dermatology-confirmed diagnoses. The aim is to determine sensitivity, specificity, and predictive value of the AI tool across diverse populations and skin tones. The study will also assess user experience, accessibility, and integration into clinical care pathways.
Interventions
DIAGNOSTIC_TESTSmartphone-based AI skin lesion analysis (NuvanaDx platform).
Smartphone-based AI skin lesion analysis (NuvanaDx platform).
Sponsors
National Institute for Health Research, United Kingdom
Nuvana Healthcare LTD
Study design
Observational model
ECOLOGIC_OR_COMMUNITY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Months to No maximum
Healthy volunteers
Yes
Inclusion criteria
Adults (≥18 years) presenting with skin lesions suspicious for malignancy. Ability to provide informed consent.
Exclusion criteria
Inability to provide informed consent. Poor-quality images unsuitable for AI analysis.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic Accuracy of AI tool compared with dermatologist-confirmed diagnosis | Time Frame: Up to 12 months | Diagnostic Accuracy of AI tool compared with dermatologist-confirmed diagnosis Time Frame: Up to 12 months Measure: Sensitivity, specificity, and predictive values |
Countries
United Kingdom
Contacts
Primary ContactSushma Saxena, Director, Nuvana Healthcare Ltd
Outcome results
None listed