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Machine Learning in Brain Tumors and Neurovascular Disease: Focus on Molecular Neuroscience

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 195

Special Issue Editors


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Guest Editor
Neurosurgery Unit, Department of Neuroscience, University of Turin, Via Giuseppe Verdi, 8, 10124 Turin, Italy
Interests: neuroncology; glioma; brain mapping; intraoperative ultrasound; intraoperative fluorescence; neuromonitoring; fiber tracking
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Neurosurgery Unit, Department of Neuroscience, University of Turin, Via Giuseppe Verdi, 8, 10124 Turin, Italy
Interests: neurobiology; neurobiology and brain physiology; neurodegeneration; synaptic plasticity; neuroanatomy; neurodegenerative diseases; neural plasticity
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

Neuroscience is a rapidly evolving field, and the development of new tools and techniques is crucial for advancing our understanding of the brain. Machine learning has emerged as a powerful tool for analyzing complex neural data, including EEG, fMRI, and single-cell recordings. By leveraging machine learning algorithms, researchers are able to extract meaningful patterns from large datasets and gain new insights into the functioning of the brain. We propose a Special Issue of the International Journal of Molecular Sciences that will highlight some of the latest developments in this area, with a focus both on the educational side, for researchers approaching this new tool, and on the clinical side, with the aim of providing a bridge between clinical and machine learning studies with papers addressing the two sides of such research.

The articles in this special issue will cover a range of topics related to machine learning in neuroscience, including novel approaches for analyzing neural data, advances in deep learning for image analysis, and the use of machine learning for clinical applications. We plan to include both original research articles and reviews, with contributions from leading experts in the field.

Dr. Andrea Bianconi
Prof. Dr. Diego Garbossa
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • machine learning
  • deep learning algorithm
  • automatic segmentation
  • brain tumor
  • molecular subtyping
  • single-cell sequencing

Published Papers

There is no accepted submissions to this special issue at this moment.
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