Neural networks and pattern recognition in medicine

Organizers:

Giansalvo Cirrincione, Université de Picardie Jules Verne, miens, France (exin@u-picardie.fr) and Vitoantonio Bevilacqua, Dept. of Electrical and Information Engineering, Polytechnic University of Bari, Italy (vitoantonio.bevilacqua@poliba.it)

Since the very beginning, artificial intelligence has been influenced by medicine, and at the same time has impacted on it very strongly. For instance, in the automatic diagnosis, as a help for doctors’ decisions, or as a tool for improving patients’ health or for biomedical signal processing and brain modelling. Neural networks and neural or statistical pattern recognition are ever increasingly important methods in this field. Also, modelling and pattern recognition help in understanding the mechanisms of diseases, like cancer. At this aim, algorithms in data mining and big data are of utmost importance.

This special session aims to illustrate the state of the art and the perspectives of the most recent techniques, both neural, as deep learning, and not, with a special stress on the biomedical image and signal processing, medical classification and diagnosis, and analysis of gene expression data. Papers in pattern recognition, especially as a support to medical diagnosis, are also welcome.