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原文連結
論文資訊
- 類型：已發表論文
- 日期：2020-01-07
摘要
Combining advanced neuroimaging with novel 計算 methods in 網絡 science and 機器學習 has led to increasingly meaningful descriptions of structure and function in both the normal and the abnormal 大腦, thereby contributing significantly to our understanding of psychiatric disorders as circuit dysfunctions. Despite its marked potential for psychiatric care, this approach has not yet extended beyond the research setting to any clinically useful applications. Here we review current developments in the study of neuroimaging data using 網絡 models and 機器學習 methods, with a focus on their promise in offering a framework for clinical translation. We discuss 3 potential contributions of these methods to psychiatric care: 1) a better understanding of psychopathology beyond current diagnostic boundaries; 2) indiv
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