Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency

Ana Barragan-Montero, Adrien Bibal, Margerie Huet Dastarac, Camille Draguet, Gilmer Valdes, Dan Nguyen, Siri Willems, Liesbeth Vandewinckele, Mats Holmstrom, Fredrik Lofman, Kevin Souris, Edmond Sterpin, John A. Lee

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

Fingerprint

Dive into the research topics of 'Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency'. Together they form a unique fingerprint.

Medicine & Life Sciences