Imaging the Brain, Complex Networks and Supervised Learning for Diagnosis Support Systems
A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Neurology".
Deadline for manuscript submissions: closed (1 November 2020) | Viewed by 267
Special Issue Editor
Interests: machine learning; deep learning; data visualization; complex networks; imaging; segmentation; big data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the study of brain models based on structural or functional magnetic resonance imaging data, especially with the help of complex network approaches, has revealed important features of neurodegenerative diseases, such as Alzheimer’s disease, but more in general have provided neuroscientists of novel tools to investigate and better understand the brain. There is a great interest in early diagnosis support systems exploiting this informative content, with a subsequent characterization of pathological patterns, especially for what concerns brain connectivity. In particular, this Special Issue strongly welcomes studies concerning methodologies and perspectives unveiling novel network properties and their relationship with the disease; given the peculiar possibility provided by medical imaging to exploit multi-modal data, we also encourage related submissions. Finally, the amount of information concealed within imaging data can easily fall within the Big Data expertise domain field. This Special Issue will also take in great consideration studies based on machine learning and deep learning approaches, considering both knowledge based on raw imaging data and novel types of knowledge such as, for example, those provided by complex networks or, more in general, connectivity models.
Dr. Nicola Amoroso
Guest Editor
Manuscript Submission Information
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Keywords
- Structural and functional MRI
- Brain connectivity
- Machine learning
- Deep learning
- Complex networks
- Multiplex
- Aging
- Neurodegenerative diseases
