SIBILA: High-performance computing and interpretable machine learning join efforts toward personalised medicine in a novel decision-making tool. (arXiv:2205.06234v1 [cs.LG])

Web: http://arxiv.org/abs/2205.06234

Background and Objectives: Personalised medicine remains a major challenge
for scientists. The rapid growth of Machine learning and Deep learning has made
it a feasible alternative for predicting the most appropriate therapy for
individual patients. However, the lack of interpretation of their results and
high computational requirements make many reluctant to use these methods.

Methods: Several Machine learning and Deep learning models have been
implemented into a single software tool, SIBILA. Once the models are trained,
SIBILA applies a range …

arxiv computing decision join learning machine machine learning making medicine performance tool