Clinical Validation Studies
This section provides full bibliographic references for the clinical validation studies cited in the Clinical Benefits and Performance Claims section. Each study code that appears alongside a performance metric is defined below with its complete study metadata.
Study-to-Benefit Cross-Reference
The following table summarises which clinical benefits each study supports. Clinical benefit codes are defined in the Clinical Benefit Identifiers section.
| Study | Clinical Benefits Supported | Claims |
|---|---|---|
 MC_EVCDAO_2019 | 7GH1QF | 12 |
 COVIDX_EVCDAO_2022 | 3KX5RB0ZC | 7 |
| DAO_Derivación_PH_2022 | 3KX8PL1QF | 3 |
 IDEI_2023 | 7GH1QF5RB | 14 |
 SAN_2024 | 7GH3KX0ZC | 31 |
 BI_2024 | 7GH9VW | 45 |
| PH_2024 | 7GH3KX9VW0ZC | 17 |
| DAO_Derivation_O_2022 | 3KX8PL1QF0ZC | 17 |
 AIHS4 2025 | 5RB | 2 |
Study Bibliography
MC_EVCDAO_2019Clinical validation study of a CAD system with artificial intelligence algorithms for early noninvasive in vivo cutaneous melanoma detection
- Primary objective: To assess the diagnostic accuracy of the Legit.Health CAD system in differentiating between benign and malignant melanocytic skin lesions.
- Study design and setting: Observational, non-interventional, prospective, multi-centre study.
- Principal investigator(s): Dr. Jesus Gardeazabal Garcia; Dr. Rosa Ma Izu Belloso
- Investigational site(s): Hospital Universitario Cruces; Hospital Universitario Basurto
- Sample size: 105 participants
- Study period: February 2020 – November 2023
- Device version: Legit.Health Legacy Device
- Publication status: Expected to be sent in May 2025 to the Journal of the European Academy of Dermatology and Venereology Clinical Practice
COVIDX_EVCDAO_2022Clinical Validation of a Computer-Aided Diagnosis (CAD) System Utilizing Artificial Intelligence Algorithms for Continuous and Remote Monitoring of Patient Condition Severity in an Objective and Stable Manner
- Primary objective: To validate the use of AI algorithms for continuous and remote monitoring of patient condition severity.
- Study design and setting: Observational and clinical prospective study conducted at Torrejón University Hospital focusing on stable and objective monitoring.
- Principal investigator(s): Dra. Marta Andreu
- Investigational site(s): Torrejón University Hospital
- Sample size: 160 participants
- Study period: April 2022 – October 2023
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
DAO_Derivación_PH_2022Project to enhance Dermatology E-Consultations in Primary Care Centres using Artificial Intelligence Tools
- Primary objective: To enhance dermatology e-consultations in primary care using AI-driven referral optimization tools.
- Study design and setting: Observational and clinical prospective study conducted at Pozuelo/Majadahonda Health Centers and Puerta del Hierro University Hospital.
- Principal investigator(s): Dr. Gastón Roustan Gullón
- Investigational site(s): Pozuelo and Majadahonda Health Centers; Puerta del Hierro Majadahonda University Hospital
- Sample size: 131 participants
- Study period: June 2022 – January 2024
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
IDEI_2023Optimisation of clinical flow in patients with dermatological conditions using Artificial Intelligence
- Primary objective: To optimize clinical workflow for patients with dermatological conditions through AI integration.
- Study design and setting: Observational, non-interventional study conducted at the Instituto de Dermatología Integral (IDEI).
- Principal investigator(s): Dr. Miguel Sánchez Viera
- Investigational site(s): Instituto de Dermatología Integral (IDEI)
- Sample size: 204 participants
- Study period: January 2024 – August 2024
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
SAN_2024Multi-Reader Multi-Case Study for Evaluating the Impact of Legit.Health Plus Device on the Healthcare Practitioners' Assessment of Skin Lesions
- Primary objective: To improve the diagnosis of various skin pathologies in a live clinical environment using non-invasive AI tools.
- Study design and setting: Prospective, multi-reader, multi-case study conducted remotely using anonymized images sent to participating healthcare professionals.
- Principal investigator(s): Dr. Antonio Martorell Calatayud
- Investigational site(s): This study was conducted remotely by sending the images to the participating professionals.
- Sample size: 29 participants
- Study period: June 2024 – October 2024
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
BI_2024Multi-Reader Multi-Case Study for Assessing the Impact of Legit.Health Plus on the Clinical Assessment of Generalised Pustular Psoriasis and Other Skin Conditions by Healthcare Professionals.
- Primary objective: To improve the diagnostic accuracy for Generalized Pustular Psoriasis in a live clinical environment.
- Study design and setting: Prospective, multi-reader, multi-case study conducted remotely by distributing images to participating dermatologists.
- Principal investigator(s): Dr. Antonio Martorell Calatayud
- Investigational site(s): This study was conducted remotely by sending the images to the participating dermatologists.
- Sample size: 100 participants
- Study period: June 2024 – September 2024
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
PH_2024Multi-Reader Multi-Case Study Assessing the Impact of Legit.Health Plus on the Diagnostic Accuracy and Referral Decision-Making of Primary Care Physicians for Skin Lesions.
- Primary objective: To evaluate and improve the diagnostic process for skin pathologies in primary care settings using AI.
- Study design and setting: Prospective, multi-reader, multi-case study conducted remotely via image analysis by participating primary care professionals.
- Principal investigator(s): Dr. Gastón Roustán Gullon
- Investigational site(s): This study was conducted remotely by sending the images to the participating professionals.
- Sample size: 30 participants
- Study period: June 2024 – September 2024
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
DAO_Derivation_O_2022Pilot study for the clinical validation of an artificial intelligence algorithm to optimize the appropriateness of dermatology referrals. (Ongoing Study)
- Primary objective: To clinically validate an AI algorithm designed to optimize the appropriateness and efficiency of dermatology referrals.
- Study design and setting: Multi-centre, observational and prospective study conducted across multiple primary health centers (Sodupe-Güeñes, Balmaseda, Buruaga, Zurbaran).
- Principal investigator(s): Dr. Jesús Gardeazabal García; Dr. Rosa Mª Izu Belloso
- Investigational site(s): Health Centre Sodupe-Güeñes; Health Centre Balmaseda; Health Centre Buruaga; Health Centre Zurbaran
- Sample size: 117 participants
- Study period: November 2022 – April 2025
- Device version: Legit.Health Plus
- Publication status: Not yet submitted for publication
AIHS4 2025Evaluation of AIHS4 Performance in the M-27134-01 Clinical Trial for Hidradenitis Suppurativa
- Primary objective: To evaluate the performance and reliability of the AIHS4 scoring system within the context of a clinical trial for Hidradenitis Suppurativa.
- Study design and setting: Observational non-interventional study based on the remote evaluation of clinical trial images.
- Principal investigator(s): Dr. Antonio Martorell Calatayud
- Investigational site(s): This study was conducted remotely based on clinical trial image evaluations.
- Sample size: 2 participants
- Study period: June 2024 – July 2024
- Device version: Legit.Health Plus
- Publication status: Published (May 2023)