Objective, reproducible dermatological endpoint scoring from smartphone images. Automated severity scoring aligned with established clinical scales for clinical trials. CE-marked Class IIa medical device.
A plain-language explanation for study subjects of what calibration markers are for, your role during the imaging visit, and what to expect.
How to calibrate a camera model before study imaging, including the calibration board, camera requirements, capture procedure, and submission process.
Legit.Health AI scoring is deployed in Phase 2 and Phase 3 clinical trials with top-10 pharma companies across 130+ sites in 12+ countries, spanning psoriasis, acne, alopecia, and atopic dermatitis.
End-to-end clinical trial workflow for acne severity endpoints, covering protocol design, patient enrollment, image capture, AI scoring, severity tracking, data export, EDC integration, and decentralised trial support.
End-to-end clinical trial workflow for SALT endpoints, covering protocol design, site setup, patient enrolment, in-clinic scalp capture, automated SALT scoring, change from baseline and alerts, data export, and EDC integration.
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.
End-to-end clinical trial workflow for hidradenitis suppurativa severity endpoints, covering protocol design, site setup, patient enrolment, in-clinic image capture, automated IHS4 and HiSCR, and EDC data export.
End-to-end clinical trial workflow for PASI endpoints, covering protocol design, site setup, patient enrolment, image capture, AI scoring, PASI response milestones, data export, and EDC integration.
How outputs are derived from each image and aggregated across images, why a defined imaging protocol is what makes composition across views possible, and the decisions a sponsor fixes before first capture.
Standardised steps for site staff to place calibration markers and capture lesion photographs, with a do and do-not checklist, how the number of detected markers is reported back, the printable one-page capture guide issued per project, correct and incorrect placement examples by condition, troubleshooting, and storage guidance.
How scalp images are captured for automated SALT scoring: the standard four-quadrant set, DIQA quality control, patient preparation, and site standardisation.
How atopic dermatitis images are captured for automated SCORAD and EASI scoring: the standard body-perspective and close-up set, DIQA quality control, patient preparation, and site standardisation.
How hidradenitis suppurativa images are captured for automated IHS4 and HiSCR: the standard capture regions, photographed only where there are lesions, framing and lighting rules, DIQA quality control, patient preparation and anonymisation.
How psoriasis images are captured for automated PASI scoring: the standard body-perspective and close-up set, DIQA quality control, patient preparation, and site standardisation.
Image capture protocols for acne clinical trials, covering smartphone-based photography, DIQA quality control, multi-perspective flexibility, facial landmark detection, and site standardisation.
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.
How calibration markers give the Legit.Health platform a known reference for measuring lesion surface area, and for calibrating colour across visits in dermatology clinical trials.
Transparent documentation of what the AI acne severity scoring can and cannot do, including scope boundaries, validation gaps, and how each limitation is managed.
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.
Transparent documentation of what the automated IHS4 scoring for hidradenitis suppurativa can and cannot do, including the constraints of photograph-based lesion counting and how each limitation is managed.
Transparent documentation of what the AI psoriasis severity scoring can and cannot do, including the inherent constraints of photograph-based PASI assessment and how each limitation is managed.
The physical specification of the Legit.Health Color Multi-Marker, its black and white borders, the 5 by 5 colour-patch grid, and the requirements a marker must meet for reliable automated detection.
Automated PASI scoring for psoriasis clinical trials. AI-powered measurement of erythema, desquamation, induration, and affected body surface area across four body regions.
Concrete examples of what sponsors, CROs, and investigators receive from acne severity assessments: per-visit AI reports with lesion detection overlays, longitudinal severity tracking, and structured EDC data exports.
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.
Technical detail on how automated lesion detection and counting produce IHS4 and HiSCR for hidradenitis suppurativa, covering lesion classification, the IHS4 formula, severity thresholds, HiSCR against baseline, and comparison with manual assessment.
Deep technical detail on the automated SCORAD and EASI scoring pipelines, covering BSA segmentation, intensity sign scoring, SCORAD and EASI formulas, severity scale, and comparison with manual assessment.
The psoriasis assessment sequence step by step, from the eleven capture screens the subject sees, through the images they submit, to the segmentation overlays the device returns, the scored PASI report format, and the automatic response-milestone alert.