SIBILA: High-performance computing and interpretable machine learning join efforts toward personalised medicine in a novel decision-making tool

The Spanish partner UCAM has deposited a preprint, which has been submitted to a journal, on the machine learning tool they have been developing, SIBILA.

SIBILA has been developed with the aim of becoming a useful and powerful decision-making tool for clinicians; in fact, it consists of a software tool (into which diverse machine learning and deep learning models have been implemented) that aims at producing accurate analyses and predictions regarding therapies for individual patients, thus dwelling into the complex field of personalised medicine. 

SIBILA, through Machine Learning (ML) and High-Performance Computing (HCP), has already been used for three different case studies which showed its efficiency in classification and regression problems and proved that this tool can be adopted in medical contexts, using real data.

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SIBILA, along with the REVERT project, has already been presented during the 2022 International CMMSE conference (Computational and Mathematical Methods in Science and Engineering) and during the Computational Chemistry Gordon Research Conference held in Spain in July 2022.

Click here for the complete report on SIBILA.


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 848098”.

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