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

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

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