机器学习在心理健康中的运用

Application of Machine Learning in Mental Health

在社会快速发展以及疫情流行的大背景下,我国民众的心理健康问题日益严重,引进新的心理监督预测技术刻不容缓。机器学习作为人工智能主要的子领域之一,可以自动从数据中学习模型以做出更好的决策。由于其计算以及预测结果相较于人工更迅速准确,今年已被多国引入心理健康领域开始运用,并在精神疾病诊断、治疗和支持、研究和临床管理等一系列领域展现其作用。本文基于现状,介绍了当前机器学习在心理健康领域的运用,以及在该领域进一步发展的期望。

In the context of rapid social development as well as epidemic epidemics, the mental health problems of our population are becoming increasingly serious and the introduction of new psychological supervision and prediction techniques is urgent. Machine learning, one of the main subfields of artificial intelligence, can automatically learn models from data to make better decisions. Because its computation, as well as prediction results, are faster and more accurate compared to human, it has been introduced into the mental health field and started to be used in several countries this year, and has demonstrated its usefulness in a range of areas such as mental illness diagnosis, treatment and support, research and clinical management. This paper presents the current use of machine learning in mental health based on the current state of affairs and the expectations for further development in this field.