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Comparison of Machine Learning Approaches for POD24 Prediction

Follicular Lymphoma (FL) is the second most common non-Hodgkin lymphoma in adults and is heterogeneous with 20% of poor-outcome patients relapsing/progressing within 24 months (POD24) of first treatment start (Casulo et al., JCO 2015). Early identification of those POD24 patients is critical but remains elusive. We initiated a collaboration between the academic CALYM Carnot Institute and the private company Euranova aiming at developing interpretable artificial intelligence (AI) models based on Positron Emission Tomography (PET) images to predict POD24.

Duc Thang Hoang, Elsa Schalck, Romain Ricci, Loïc Chartier, Léa Marlot, Bertrand Nadel, Emmanuel Gomez, Franck Morschhauser, Luc Xerri, Salim Kanoun, Cédric Rossi, Comparison of Machine Learning Approaches for POD24 Prediction, In Proc. of The International Conference on Malignant Lymphoma, June 2023.

Click here to access the paper.

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