Vázquez Lema, DavidHernández-Pereira, ElenaMosqueira-Rey, Eduardo2026-04-152026-04-152023D. Vázquez-Lema, Elena Hernández-Pereira, and E. Mosqueira-Rey, "Evaluating Curriculum Learning Strategies for Pancreatic Cancer Prediction", ESANN 2023 Proceedings - 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2023, p. 357-362, https://doi.org/10.14428/esann/2023.ES2023-141978-2-87587-088-9https://hdl.handle.net/2183/47990Presented at: ESANN 2023 - 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium, 04 - 06 October, 2023[Abstract]: In this work we applied Curriculum Learning (CL) to evaluate the performance of a machine learning (ML) model for pancreatic cancer prediction. As the dataset required it, we applied missing value imputation and data augmentation techniques. We compare different curriculum configurations in terms of pacing functions and we perform different experiments concluding that CL helps to train the ML model. Nevertheless, not all the configurations behave in the same way, and the best results were obtained when organising the curriculum in increasing levels of difficulty following exponential pacing.eng© ESANN 2023. All rights reserved. This is the published version of the paper, distributed in accordance with ESANN's self-archiving policy, which allows authors to archive their work in any repository provided that full reference is made to the ESANN publication.Curriculum LearningPancreatic CancerMachine Learningconference outputopen access10.14428/esann/2023.ES2023-141