2019 年 36 巻 4 号 p. 159-161
In the field of psychiatry, there is a lack of biomarkers that are directly applicable in diagnostic settings or that clearly reflect illness severity. Due to this issue, it is often unclear how to best begin treatment, and patients' responses to treatment can be difficult to understand. In recent years, there has been a global effort to utilize information and communication technology, and to use machine learning to analyze Big Data collected through those means, in the hopes of finding biomarkers that can be used in the diagnosis of and severity evaluations for psychiatric illnesses. In this paper, we will introduce prior research that particularly focuses on using wearable devices to evaluate depression, as well as our efforts to attempt to use multiple modalities in the screening of and severity assessments for depression.