Artificial Intelligence in Neurodegenerative diseases

Abstract

AI allows for automated data interpretation and decision-making. The peculiarity of AI is to be able to learn from data to acquire knowledge, represent and process information related to the task it has to perform, thereby overcoming the difficulty to assimilate and extract valuable information from large datasets. Thus, AI can be used as a powerful tool in the elaboration of biomedical data for the development of predictive models. One of the most relevant data sources for AI comes from the biomedical field, and the ability of DL- one of AI’s most important branches, alongside ML- to automatically learn complex representations from data is showing to be particularly promising to help ND research and clinical management Neurodegenerative diseases have shown an increasing incidence in the older pop-ulation in recent years. A signi cant amount of research has been conducted to characterize these diseases. Computational methods, and particularly machine learning techniques, are now very useful tools in helping and improving the di-agnosis as well as the disease monitoring process. In this paper, we provide an in-depth review on existing computational approaches used in the whole neu-rodegenerative spectrum, namely for Alzheimer's, Parkinson's.