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Case-Based Reasoning for the optimization of cognitive rehabilitation on TBI
Jan 2013 - Dec 2015
Project description

Acquired Brain Injury (ABI) constitutes a major and increasing social and healthcare concern of high diagnostic and therapeutic complexity. Its incidence and survival rate after the initial critical phases makes it a prevalent problem that needs to be addressed. ABI patients frequently suffer from a series of cognitive disorders related to memory, attention, language, or executive functions. Cognitive rehabilitation aims to reduce the impact of the disabling conditions in order to reduce functional limitations and increase patient's autonomy. For the rehabilitation process to be more effective, treatments must be intensive, personalized to the patient's condition and evidence-based; and require constant monitoring. The main goal of the IIIA team is the research on new machine learning/CBR techniques able to propose and revise personalized therapies in real-time.

Research Line
Machine Learning for Healthcare