心理健康
心理干预
数字健康
心理学
干预(咨询)
自然(考古学)
社会化媒体
计算机科学
人工智能
医疗保健
人机交互
应用心理学
数据科学
万维网
心理治疗师
精神科
考古
经济
历史
经济增长
标识
DOI:10.1016/j.copsyc.2020.04.005
摘要
With the advent of digital approaches to mental health, modern artificial intelligence (AI), and machine learning in particular, is being used in the development of prediction, detection and treatment solutions for mental health care. In terms of treatment, AI is being incorporated into digital interventions, particularly web and smartphone apps, to enhance user experience and optimise personalised mental health care. In terms of prediction and detection, modern streams of abundant data mean that data-driven AI methods can be employed to develop prediction/detection models for mental health conditions. In particular, an individual's 'digital exhaust', the data gathered from their numerous personal digital device and social media interactions, can be mined for behavioural or mental health insights. Language, long considered a window into the human mind, can now be quantitatively harnessed as data with powerful computer-based natural language processing to also provide a method of inferring mental health. Furthermore, natural language processing can also be used to develop conversational agents used for therapeutic intervention.
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