Publications, References, and Further Reading
Primary publication
APASI: Automatic Psoriasis Area and Severity Index
Mac Carthy T, Dagnino D, Medela A, Fernández G, Aguilar A, Martorell A, Gómez-Tejerina P, Roustán-Gullón G “Artificial Intelligence-Based Quantification to Assess the Automatic Psoriasis Area and Severity Index” JEADV Clinical Practice. 2025. doi:10.1002/jvc2.70143
JEADV Clin Pract. 2025
- APASI provides a robust AI-driven framework for psoriasis severity assessment
- Delivers rapid, objective, and precise evaluations of all PASI components
- Integration into clinical and research workflows enhances disease monitoring
- Reduces evaluation costs compared to manual multi-reader assessments
This is the foundational publication for the automated PASI scoring methodology, published in JEADV Clinical Practice.
Image quality assessment
DIQA: Dermatology Image Quality Assessment
Hernández Montilla I, Mac Carthy T, Aguilar A, Medela A “Dermatology Image Quality Assessment (DIQA): Artificial intelligence to ensure the clinical utility of images for remote consultations and clinical trials” Journal of the American Academy of Dermatology. 2023. doi:10.1016/j.jaad.2022.11.002
J Am Acad Dermatol. 2023;88(4):927-928
- Pearson correlation ≥0.70 with expert image quality assessment
- Real-time evaluation of focus, lighting, framing, and resolution
- Critical for standardising image quality in multi-center psoriasis trials
DIQA is particularly important for psoriasis full-body imaging, where lighting consistency and framing quality directly impact the accuracy of erythema assessment and BSA segmentation.
Conference presentations
AEDV (Spanish Academy of Dermatology and Venereology) 2025, Valencia
Oral communication: AI-based quantification to assess the automatic area and severity index of psoriasis
Oral presentation of the APASI methodology — automated PASI scoring via AI-driven quantification of erythema, desquamation, induration, and body surface area from clinical images.
EADV (European Academy of Dermatology and Venereology) 2025, Paris
Poster: APASI: Automatic Psoriasis Area and Severity Index with AI-driven quantification
Scientific poster presenting the APASI system — automated PASI scoring with component-level validation against expert inter-rater variability, demonstrating non-inferiority across all four PASI components.
Key references from the literature
Fredriksson T, Pettersson U “Severity assessment of psoriasis in an international cross-sectional study” Dermatologica. 1978.
Original publication defining the PASI scoring system. Establishes the four-region, three-component methodology that remains the standard for psoriasis clinical trials.
U.S. Food and Drug Administration “Psoriasis: Developing Drug Products for Treatment. Guidance for Industry.” FDA Guidance Document. 2022.
FDA guidance establishing PASI 75/90/100 response rates and IGA as the primary endpoints for psoriasis drug development.
Clinical validation portfolio
Legit.Health maintains an active clinical validation program across all supported conditions. The complete evidence portfolio is available in the clinical validation section.
Commencez maintenant
Dermatologie basée sur l'IA validée par des recherches évaluées par des pairs. Approuvée par les principaux hôpitaux européens. Remplissez le formulaire pour découvrir comment notre plateforme certifiée CE peut transformer votre pratique.