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20072026
most citedWhen will the mist clear? On the Interpretability of Machine Learning for Medical Applications: a survey

72 citations

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cs.LG2025★ 1 cited

WISCA: A Consensus-Based Approach to Harmonizing Interpretability in Tabular Datasets

Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez, Carlos Martínez-Cortés

While predictive accuracy is often prioritized in machine learning (ML) models, interpretability remains essential in scientific and high-stakes domains. However, diverse interpret…

cs.LG2022★ 1 cited

SIBILA: A novel interpretable ensemble of general-purpose machine learning models applied to medical contexts

Antonio Jesús Banegas-Luna, Horacio Pérez-Sánchez

Personalized medicine remains a major challenge for scientists. The rapid growth of Machine learning and Deep learning has made them a feasible al- ternative for predicting the mos…