A Cognitive Computing Tool for Identification and Classification of Brain Tumors

This paper describes results of the research activities carried out within the PhD in Information and Communication Technology for Health (ICTH) on the topic of Delivery Manager of Cognitive Computing for Neuroncology at the Department of Electrical Engineering and Information Technologies (DIETI) of the University of Naples “Federico II”. Aims of this paper is the evaluation of an innovative computational system based on cognitive computing technologies, namely the open-source PyTorch-based deep learning framework for medical data named FuseMedML, for the analysis of magnetic resonance (MRI) imaging derived data in patients with brain neoplasm of unknown origin; main goal is to obtain a supervised binary classification model which allows the timely identification of the two most common malignant brain tumors of the adulthood, requiring therapeutic strategies and clinical-radiological monitoring different the one from the other.