Tag: machine learning in mental health

Depression affects hundreds of millions of people worldwide, yet the deep learning systems that promise to flag it early have ...

A machine learning study of junior high students in Shanghai finds that negative low-arousal academic emotions are the strongest predictor ...

A new EEG study finds that altered transitions between the brain's brief electrical microstates, combined with source-space connectivity features, can ...

A systematic review of 27 studies and 58 prediction models finds that algorithms for forecasting adolescent non-suicidal self-injury show moderate ...

Researchers trained a convolutional neural network to detect and characterize eating disorder discourse on Weibo, uncovering five major themes in ...

A comprehensive review of 69 studies shows that machine learning and deep learning models can diagnose depression from EEG and ...

Researchers trained interpretable machine learning models on pandemic-era survey data to classify healthcare workers by psychological resilience, finding stress, depression, ...

Recent scientific advancements have ushered in a new era for the diagnosis of emotional-behavioral disorders, especially in the context of ...

In recent years, nonsuicidal self-injury (NSSI) among adolescents and young adults has emerged as a pressing public health concern, with ...

In recent years, the intersection of mental health education and artificial intelligence has opened new avenues for enhancing educational strategies ...