Please provide your email address to receive an email when new articles are posted on . Ensemble machine learning models may predict secondary treatment for depression that does not respond to ...

Using the neuroimaging data from a prior case-control study of patients with MDD and healthy control individuals, researchers conducted a systemic simulation classification in various scenarios to ...

Background and goal: Depression impacts an estimated 18 million Americans each year, yet depression screening rarely occurs in the outpatient setting. This study evaluated an AI-based machine learning ...

In a recent study published in Scientific Reports, researchers established a benchmark classification of major depressive disorder (MDD) using machine learning (ML) on cortical and subcortical ...

Postpartum depression (PPD) affects up to 15 percent of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Researchers ...

After giving birth, new mothers typically return for a follow-up appointment six to eight weeks later. But if postpartum depression symptoms emerge, “that can be a really long time for someone who is ...

Please provide your email address to receive an email when new articles are posted on . The model demonstrated a high degree of predictability for postpartum depression. Of those predicted to have a ...

The machine-learning method identified key functional connections in the imaging data that could serve as a brain network signature for major depression. Indeed, when the researchers applied that new ...

As a way to investigate the relationship between depression and language, the approach taken so far was that researchers read the notes of actual subjects and take notes. Naturally, because it is an ...

Radial reports that teen depression is prevalent yet under-treated. Effective options include therapy, antidepressants, and ...