Prospective, cross-sectional, multicentre diagnostic accuracy study (2020)
Conducted at two dermatology outpatient clinics in the Netherlands (Erasmus MC Cancer Institute & Albert Schweitzer Hospital)
Each lesion was first examined by a clinician, then assessed using the SkinVision app (iOS or Android)
App risk outcomes were compared to histopathology (when indicated) or dermatologist diagnosis
Reporting followed Standards for Reporting Diagnostic Accuracy (STARD) 2015 guidelines1
Adults ≥18 years with ≥1 suspicious skin lesion
Excluded: prior biopsy, unclear diagnosis, technical failures, or inability to consent
785 lesions (from 372 patients)
Median age: 71 years
Gender: 50.8% women
Fitzpatrick skin type: >80% type I–II
Sensitivity and specificity of the SkinVision app in detecting premalignant and malignant lesions.
The SkinVision app correctly identified 239 of the 275 (pre) malignant lesions as high-risk
The Specificity of the SkinVision app was set at 80.1% (based on benign control lesions)
Sensitivity by cancer type2:
Premalignant lesions (n=131)
Overall results:
The SkinVision app correctly identified 239 of the 275 (pre) malignant lesions as high-risk
The Specificity of the SkinVision app was set at 80.1% (based on benign control lesions)
Sensitivity by cancer type2:
Premalignant lesions (n=131)
Overall results:
- The SkinVision app achieved high sensitivity (86.9%) and specificity (80.1%) for detecting skin (pre)malignancies in a clinical setting – performance that is comparable to experienced dermatologists (sensitivity 76.9%, specificity 89.1%)3.
- These findings support the app’s potential as a reliable self-assessment and triage tool, while also highlighting the need for further validation in lay users and across diverse skin types.
