The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now well established by magnetic resonance imaging (MRI) studies. To create diagnostic and prognostic tools, as well as identifying biologically valid subtypes of BD, research has recently turned towards the use of machine learning (ML) techniques. We assessed both supervised ML and unsupervised ML studies in BD to evaluate their robustness, reproducibility and the potential need for improvement.

中文翻译：

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将机器学习应用于双相情感障碍的神经影像学会对临床医生有所帮助吗？严格审查和方法建议。

现在，通过磁共振成像（MRI）研究已经很好地确定了双相情感障碍（BD）的解剖功能性脑部异常的存在。为了创建诊断和预后工具以及识别BD的生物学有效亚型，最近的研究转向使用机器学习（ML）技术。我们评估了BD的有监督的ML和无监督的ML研究，以评估其鲁棒性，可重复性以及潜在的改进需求。