Jose M. Juarez, PhD
Assoc. Professor & Project Leader, University of Murcia
We investigate how to enhance doctors’ understanding of Machine Learning (ML) and the use of Open Data. We also develop an ML-based antibiotic recommender system based on Continual Learning using Open Data. The system support explainability by design through the incorporation of an educational platform that make all the steps of the ML pipeline transparent, accurate and robust.
We identify the best interplay mechanisms for epidemiological AI-based simulations for patient isolation and outbreak forecasting. We develop an interactive simulator which key elements are spatio-temporal series forecasting and graph-based reasoning. We investigate the personalised communication and visualization of spatial-temporal outbreak representations adapted to each user profile.
We shall investigate how to improve doctors’ confidence in algorithms with which to obtain phenotypes for precision medicine. We shall extend and adapt subgroup discovery algorithms and clustering techniques to obtain a better description of patients at risk of infection based on information theory and redescription mining, extended with clinical events traceability, avoidance of unfair bias, and full reproducibility for scientific purposes.
We shall describe specific frameworks and guidelines for the integration of explainable AI into healthcare systems to help future generations of decision-makers to compare the most trustworthy AI-based systems
Multidisciplinary team of researchers from the University of Murcia, Regional Health Service of Murcia, University Hospital Reina Sofia, University Hospital Morales Meseguer, Maribor University and the University of Verona.
Years (1-2-3)
Publications
Patents/Copyright
Visits
These are our recent achievements from the academic, scientific and social point of view.
