Dear colleagues, We invite researchers, neuroscientists, and machine learning experts to contribute to our Research Topic "*Machine Learning Algorithms for Brain Imaging: New Frontiers in Neurodiagnostics and Treatment*". Accepted articles will be published in the journal Frontiers in Neuroinformatics. https://www.frontiersin.org/research-topics/62418/machine-learning-algorithm... *Submissions now open! * Manuscript Submission Deadline: 15 September 2024 Feel free to contact me for further info. This Frontiers Research Topic focuses on, but not limited to, the following themes: - Development and validation of novel machine learning algorithms for brain image analysis. - Deep learning techniques for brain image segmentation, classification, and feature extraction. - Predictive modeling and prognostication using machine learning to guide neurotherapeutic decisions. - Transfer learning and domain adaptation approaches in neuroimaging analysis. - Explainable AI and interpretable machine learning methods for transparent and trustworthy brain image interpretation. - Integration of multimodal imaging data (e.g., MRI, fMRI, PET) through innovative machine learning strategies. - Evaluation and benchmarking of machine learning algorithms in neuroimaging. - Current challenges, future directions, and ethical considerations in the application of machine learning algorithms in brain imaging. We welcome original research articles, comprehensive reviews, and perspectives that contribute to the field of machine-learning algorithms for brain imaging. Manuscripts should present novel methodologies, rigorous validation, and practical applications. Cheers, Shailesh Appukuttan Shailesh APPUKUTTAN *RECHERCHE > INT* Aix-Marseille Université - Campus Timone, INT NEUROSCIENCES,27 Boulevard Jean Moulin, Marseille, 13005 Site : https://shailesh-appukuttan.com/ - Email : shailesh.APPUKUTTAN@univ-amu.fr *Afin de respecter l'environnement, merci de n'imprimer cet email que si nécessaire.*