Artificial Intelligence and Pattern Recognition Methods for the Automatic Detection and Evaluation of Neurological Disorders, 2nd Edition

Dear Colleagues,

This Special Issue focuses on novel studies about neurodegeneration, which is a major problem worldwide. It is estimated that about 50 million people suffer from neurodegenerative diseases, and the number is expected to increase to 115 million by 2050. This Special Issue is focused on contributions addressing two of the main challenges that exist when studying neurodegeneration: (i) diagnosis and (ii) monitoring.

The development of modern methods in machine learning and pattern recognition has enabled the possibility of performing accurate and non-intrusive detection and monitoring of different diseases, considering the different sources of information, including speech production, language, movement, gait, handwriting, video, neural activity (EEG, electroenvephalography), and others. The use of information from these biosignals together with the development of classical and/or modern machine learning and deep learning algorithms is welcomed.

This Special Issue will focus on, but is not limited to, the following topics:

    Classical and modern machine learning methods to detect and monitor neurodegenerative diseases;

    Methods to classify different neurodegenerative diseases;

    Monitoring of disease progression;

    Evaluation of different treatment strategies, e.g., medication intake, therapy, and others;

Non-intrusive evaluation and monitoring of neurodegenerative disorders.

Prof. Dr. Juan Rafael Orozco-Arroyave
Guest Editor

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