Independent Assessment of the WHO Skin NTDs App: A Suitable Tool for Leprosy Detection

Objective To independently evaluate the World Health Organization (WHO) Skin Neglected Tropical Diseases (NTDs) app as a clinical decision-support tool for detecting leprosy. The primary objective was to determine whether leprosy appeared within the model's Top-5 diagnostic predictions. A secondary objective was to qualitatively analyse diagnostic error patterns. Methods We used a dataset of 439 anonymised clinical images from confirmed leprosy cases (1996–2024), spanning the full Ridley-Jopling spectrum, type 1 and type 2 reactions, and atypical presentations. After excluding 16 images due to processing errors, 423 images were retained: 367 classical leprosy lesions and 56 reactional or atypical leprosy-related presentations. All images were evaluated via the WHO DHIS2 interface. We estimated Top-5 sensitivity (recall) for leprosy and performed a qualitative error analysis focusing on intra-patient inconsistencies and challenging lesion types. Findings: The model achieved an overall Top-5 sensitivity (recall) of 84.9%, with higher sensitivity for classical lesions (87.2%) than for reactional or atypical presentations (69.6%). Qualitative review revealed inconsistent predictions for visually similar lesions from the same patient, and misclassifications concentrated among necrotic, inflammatory, and infiltrative lesions. Conclusion The WHO Skin NTDs app demonstrates substantial promise as a clinical decision-support and educational tool, especially for classical leprosy. Performance gaps for reactional and atypical forms highlight the need for algorithmic refinement. Enhancing dataset diversity, incorporating lesion segmentation, and integrating patient-level context may improve diagnostic robustness.