精神病学中的先进机器学习方法：引言

Wu Tsung-Chin, Zhou Zhirou, Wang Hongyue, Wang Bokai, Lin Tuo, Feng Changyong, Tu Xin M

Department of Mathematics, University of California San Diego, La Jolla, California, USA.

Department of Biostatistics and Computational Biology, University of Rochester, Rochester, New York, USA.

Gen Psychiatr. 2020 Mar 16;33(2):e100197. doi: 10.1136/gpsych-2020-100197. eCollection 2020.

Mental health questions can be tackled through machine learning (ML) techniques. Apart from the two ML methods we introduced in our previous paper, we discuss two more advanced ML approaches in this paper: support vector machines and artificial neural networks. To illustrate how these ML methods have been employed in mental health, recent research applications in psychiatry were reported.

心理健康问题可以通过机器学习（ML）技术来解决。除了我们在上一篇论文中介绍的两种机器学习方法外，我们在本文中还将讨论另外两种更先进的机器学习方法：支持向量机和人工神经网络。为了说明这些机器学习方法是如何应用于心理健康领域的，我们报告了近期在精神病学中的研究应用。