Machine Learning

Technology is allowing new strategies to reduce the risk of suicide using AI. This article explores some of these innovative developments and some concerns.

Mental health conditions are a substantial global health issue that’s continuously increasing. Soul Machines Digital People can, and do deliver mental health support in a uniquely kind and inclusive way – patients and clients feel seen and heard in a judgment-free space.

Universal screening in emergency departments (EDs) has […] led to a near 2-fold increase in suicide risk detection in adults. Predictive models might augment face-to-face screening and leverage electronic health record (EHR) data toward the automated, early detection of individuals at risk of suicide.

Researchers developing treatments for addiction are turning to virtual reality and gaming to help patients overcome their lack of impulse control and decrease the relapse rates. Participants who completed the training were found to perform better than control groups in a classical task used to test inhibition.

“Researchers are learning more about how therapy works by examining the language therapists use with clients. It could lead to more people getting better, and staying better. Researchers have tried to study talking therapy for years to unlock the secrets of why some therapists get better results than others.

Loneliness is a growing public health issue that has been exacerbated in vulnerable groups during the COVID-19 pandemic. Computer agents are capable of delivering psychological therapies through the internet, however, there is little research on their acceptability to date.

Through video calls, Opsis Emotion AI’s software will be used by counsellers to help diagnose mental health conditions such as anxiety, stress and depression. Emotional analysis technology developed by software solutions provider Opsis Emotion AI will be piloted over the next two years.