Projet financé
Prédicteurs cliniques et basés sur des biomarqueurs des résultats chez les patients atteints de cancer du poumon non à petites cellules avancé traités en première ligne par inhibiteurs de checkpoints, avec ou sans chimiothérapie à base de platine
Silvia Masini • IRCCS Humanitas Research Hospital
Résumé
Obiettivo generale
• To generate adequate synthetic data from a real-world cohort of well-annotated consecutive LC patients using GANs and other generative models • To validate the synthetic data generated with a validation framework in terms of statistical fidelity, clinical utility and privacy preservability.
Risultati attesi
We expect to generate high-fidelity synthetic datasets that reliably reproduce the statistical distribution and clinical complexity of real-world NSCLC cohorts. Validated through the SAFE and MOSAIC frameworks, the models will demonstrate improved ability to predict outcomes in first-line immunother…
Données clés
- Durée : 24 mois
- Financement : €3.000
- Centre : IRCCS Humanitas Research Hospital