This session focuses on original and new research results regarding the broad and fascinating field of data analysis on the health domain. Thus, manuscripts on data cleansing, data wrangling, data modeling, signal processing, text processing, data mining and their application to health, are solicited. Submissions addressing critical up-to-date reviews will also be welcome.
Special emphasis will be given to methods for analysis of those complex data. Statistical methods (basic, PCA, correlation, regression …), network analysis (entropy, Granger causality,.. ), visualization, traditional AI methods (decision trees, random forests, SVM, boosting, bagging, …), stream analysis methods, databases approaches, clustering approaches (hierarchical, distance based, … ), knowledge graph analysis and ontologies to enrich semantics or deep learning and the exploration of their relation between these techniques and probability theory, information theory, and entropy will be of special interest.