Dear Colleagues,

Artificial intelligence and machine learning can change the way we think of health care from many perspectives. One application, in particular, concerns developing computer-aided diagnosis systems to provide clinicians with novel non-invasive and low-cost support tools. These systems can have a crucial role, especially if we consider degenerative brain disorders, such as Parkinson’s disease and Alzheimer’s disease, which represent a really growing health problem. At the early stages of these diseases, the patient may be characterised by minimal changes, not enough to meet the standard criteria for a specific pathology. Predictive models come in handy as they can detect subtle but meaningful patterns, which may be overlooked by the human expert.

Significant advancements in this context have been obtained, in the last years, in neuroimaging, particularly functional magnetic resonance imaging and diffusion weighted imaging. More recently, a growing research interest has arisen towards the application of behavioural biometric traits. Examples include handwriting, speech and gait. The aim of this Special Issue is to bring together researchers from neuroscience and biometrics, improving the relationship between these two research communities. This Special Issue calls for original manuscripts proposing artificial intelligence and machine learning methods, based on neuroimaging as well as biometric traits, for neurodegenerative diseases assessment. Therefore, research proposing multimodal approaches, exploring data of diverse nature, is especially welcome.

Dr. Gennaro Vessio
Dr. Eufemia Lella
Dr. Rosa Senatore
Guest Editors

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• Neurodegeneration
• Biomarkers
• Machine learning
• Deep learning
• Computer-aided diagnosis
• Neuroimaging
• Handwriting analysis
• Speech analysis
• Gait analysis
• Multimodal approaches