siyi-wind/FairDisCo

[ECCV ISIC Workshop 2022 (best paper)] FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning (an official implementation)

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Experimental

This project helps dermatology researchers and AI model developers build fairer AI systems for diagnosing skin diseases. It takes existing skin lesion images (like those from Fitzpatrick17k or DDI datasets) and outputs a more equitable AI model. The end-user persona is an AI researcher or machine learning engineer working on medical imaging in dermatology.

No commits in the last 6 months.

Use this if you are developing AI models for dermatology and want to ensure they perform consistently across different patient demographics and skin types, reducing bias in diagnoses.

Not ideal if you are a clinician looking for a ready-to-use diagnostic tool, as this project focuses on the underlying model development for fairness.

dermatology-AI medical-imaging algorithm-fairness skin-lesion-analysis computational-dermatology
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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Last pushed

Apr 20, 2023

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