RecruitingNCT06621810

Artificial Intelligence Based Melanoma Early Diagnosis and Risk Prediction in Children, Adolescents and Young Adults

AI-MEL: Image Analysis and Machine Learning for Early Diagnosis and Risk Prediction in Children, Adolescents and Young Adults


Sponsor

German Cancer Research Center

Enrollment

3,000 participants

Start Date

Dec 1, 2022

Study Type

OBSERVATIONAL

Conditions

Summary

The goal of this study is to develop supportive diagnostic artificial intelligence algorithms to distinguish melanoma from nevi or other benign pigmented skin lesions, especially in younger patients (below the age of 30). The main goals it aims to achieve are: * development of an algorithm based on dermatoscopic images, targeting skin cancer screening in vulnerable populations * development of another algorithm based on histological images, intended to be used by pathologists on lesions that are still suspicious of melanoma after dermatologic assessment * implementation of explainability methods to enable the user to better comprehend the systems' decisions, avoid biases and increase trust in these applications There is no additional time commitment for the study participants for this study, as the data used in this project will be collected in routine clinical practice anyway.


Eligibility

Plain Language Summary

Simplified for easier understanding

This study is evaluating an artificial intelligence (AI) tool designed to help detect melanoma (a serious type of skin cancer) early and support doctors in making treatment decisions. Researchers are assessing how accurately the AI can identify melanoma versus benign (non-cancerous) moles. **You may be eligible if...** - You have a diagnosis of melanoma or a nevus (mole) being evaluated - The images of your skin lesion are of adequate quality **You may NOT be eligible if...** - You do not have a diagnosis of melanoma or a nevus - Your skin lesion images are of poor quality Talk to your doctor to see if this trial is right for you.

This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.

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Locations(3)

University of Tübingen

Tübingen, Germany

University of Florence

Florence, Italy

Hospital Clínic de Barcelona

Barcelona, Spain

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NCT06621810


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