Clinical trial · Observational
Application of Genomic Techniques and Image Processing Using Artificial Intelligence to Obtain a Predictor Model Risk of Melanoma
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The aim of this study is to develop a predictive model of risk of developing melanoma. The investigators will used artificial intelligence techniques to analysed images patterns obtained by clinical and dermoscopic pictures. The investigators want to defined a new predictive risk model obtained from genetic information and image analysis of pigmented lesions. This model could help to discriminate more accurately those patients who are most likely to develop melanoma in a high-risk population.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Melanoma | Melanoma | ONTOLOGY_EXACT | 0.98 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (0)
[]Primary outcomes (1)
- measure
- Number of participants with Melanoma
- timeFrame
- Three years
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * ≥18 years of age; * Followed up patients in the Pigmented Lesions Unit at Reina Sofia University Hospital with high risk of developing melanoma (First-degree family/personal history of familiar melanoma and/or melanocyticnevi above 50 and/or dysplastic or atypical nevi); * All nevi for which there is at least one dermatoscopy registry will be included. Exclusion Criteria: * not enough data in the patient clinical history; * located lesions on the face, scalp, mucous membrane or on acral área; * nodular or metastatic melanoma diagnosis * type V or VI of Fitzpatrick phototyping scale
References
Publications (0)
Data not yet available