• Neuroimaging Clin. N. Am. · Nov 2017

    Review

    Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

    • John M Billings, Maxwell Eder, William C Flood, Devendra Singh Dhami, Sriraam Natarajan, and Christopher T Whitlow.
    • Radiology Informatics and Image Processing Laboratory (RIIPL), Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA; Division of Neuroradiology, Department of Radiology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
    • Neuroimaging Clin. N. Am. 2017 Nov 1; 27 (4): 609-620.

    AbstractMachine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances.Copyright © 2017 Elsevier Inc. All rights reserved.

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