End-to-end workflow for cutaneous lupus erythematosus severity endpoints, covering retrospective image analysis versus prospective CLASI reconstruction, protocol design, capture, scoring, review, longitudinal tracking, and EDC data export.
Automated CLASI scoring for cutaneous lupus erythematosus clinical trials. AI quantification of the visual components of CLASI Activity and CLASI Damage across 13 anatomical regions, plus a continuous repigmentation measure, from smartphone images. CE-marked medical device.
Image capture protocol for cutaneous lupus erythematosus clinical trials, covering the 13-region CLASI capture set, target lesions, the metadata required to assemble a CLASI score, DIQA quality control, colour and scale calibration for erythema, pigmentation and lesion area, and facial anonymization.
Transparent documentation of what AI CLASI component scoring can and cannot do in cutaneous lupus erythematosus, covering the items not derived from an image, the scarring and alopecia boundaries, region traceability, skin phototype, and CLE-specific validation status.
What sponsors, CROs and investigators receive from a cutaneous lupus erythematosus assessment. A per-visit report with real device outputs, the repigmentation signal CLASI-D cannot express, segmentation overlays, and structured EDC export fields.
Item-by-item technical detail on how the AI quantifies the CLASI Activity and CLASI Damage components, the 13-region structure, scale alignment between sign models and CLASI item scales, and how per-image values aggregate into a CLASI score.