Depression is a complex and often chronic illness. Improving health outcomes in depression begins with improving characterization of the illness in those affected. Ecological momentary assessment (EMA) provides opportunity for passive and ambient collection of data that EMA devices suggest can determine whether a patient is depressed or not. Notwithstanding the availability of multiple app-based technologies, most require patient direct entry of some sort which the literature indicates will be insufficient from the point of view of adherence. Passive collection of data does not require any direct entry by the end user and has the ability to inform not only the person living with the illness but also their healthcare providers whether their illness is active and requires treatment. It may also be able to determine whether persons at greater risk of suicide which is being looked at with future research. This presentation will discuss the role of technology in the detection, treatment and management of mental disorders with a focus on depression and the role of artificial intelligence (AI) in treatment discovery and clinical care.
Chairperson: Kang Sim, Singapore
