47 docs tagged with "Clinical trials"

Automated inflammatory lesion counting, spatial density, an IGA-scale severity score and ALADIN for acne clinical trials, from standardised photographs of the face. CE-marked medical device.

Objective, reproducible dermatological endpoint scoring from smartphone images. Automated severity scoring aligned with established clinical scales for clinical trials. Class IIb medical device certified under the EU MDR.

Automated SALT scoring for alopecia clinical trials. AI-powered measurement of scalp hair loss across the four SALT quadrants from standardised photographs. CE-marked medical device.

Automated SCORAD and EASI scoring for atopic dermatitis clinical trials. AI-powered automated SCORAD and EASI severity assessment across body areas, validated in JID Innovations (2022). CE-marked 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.

Evidence behind automated acne scoring, covering the peer-reviewed ALADIN study against expert dermatologists, the validation of the inflammatory lesion detector, the DIQA image quality gate, the post-market clinical follow-up, and the foundational acne references.

Evidence behind automated SALT scoring for alopecia, covering the validation of the hair loss segmentation model, the DIQA image quality gate, conference presentations, and the foundational SALT references.

Peer-reviewed publications behind automated SCORAD and EASI scoring for atopic dermatitis, including the primary automated-SCORAD study and the foundational SCORAD and EASI references.

Peer-reviewed publication behind automated IHS4 scoring for hidradenitis suppurativa, covering the AIHS4 study, the DIQA image quality gate, and the foundational IHS4 and HiSCR references.

Peer-reviewed publications and production validation behind automated PASI scoring for psoriasis, covering the peer-reviewed validation study, the DIQA image quality gate, and per-component performance against expert inter-rater variability.

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 endpoints, covering protocol design, site setup, patient enrolment, facial image capture, automated lesion counting and ALADIN scoring, IGA success against baseline, data export, and EDC integration.

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 clinical trial workflow for atopic dermatitis severity endpoints, covering protocol design, patient enrolment, image capture, AI scoring, severity tracking, 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.

ISO 13485 certified, ISO 27001 compliant, GDPR, HIPAA, and 21 CFR Part 11. Audit trails, EU data residency, model version locking, and GCP compliance for clinical trials.

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.

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.

Automated IHS4 and HiSCR for hidradenitis suppurativa clinical trials. AI detection and classification of inflammatory nodules, abscesses and draining tunnels, confirmed by the investigator. CE-marked medical device.

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 facial images are captured for automated acne scoring: the standard two-diagonal set, DIQA quality control, patient preparation, and site standardisation.

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 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, the status of the clinical evidence, skin type representation, and how each limitation is managed.

Transparent documentation of what the AI alopecia severity scoring can and cannot do, including segmentation challenges, validation status, and how each limitation is managed.

Transparent documentation of what the automated SCORAD and EASI scoring can and cannot do, including the inherent constraints of photograph-based assessment 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.

AI performance validated across Fitzpatrick skin types I–VI. 280,000+ training images with published stratified performance metrics and ongoing fairness monitoring.

Automated PASI scoring for psoriasis clinical trials. AI-powered measurement of erythema, desquamation, induration, and affected body surface area across four body regions.

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 device quantifies the CLASI Activity and CLASI Damage components, the 13-region structure, scale alignment between sign models and CLASI item scales, how per-image values aggregate into a CLASI score, and how the CLA-IGA-R is supported by capturing the investigator's grade and by estimating items from automatically measured visible signs.

Technical detail on the automated PASI pipeline, covering affected-area segmentation, intensity scoring of erythema, desquamation and induration, the PASI formula, the severity scale, and comparison with manual scoring.

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.

How the AI scores acne from photographs of the face, covering inflammatory lesion detection, spatial density, the ALADIN formula on the IGA scale, response definitions, a worked example, and comparison with manual assessment.

Technical detail on how pixel-level hair loss segmentation produces the SALT score for alopecia, covering the four scalp quadrants and their weights, the SALT formula, severity bands, responder definitions against baseline, a worked example, 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.