Examining differences in brain metabolism associated with childhood maltreatment and suicidal attempt in euthymic patients with bipolar disorder: A PET and Machine Learning Study.

Dante DuarteManuel SchützeMazen ElkhayatMaila de Castro NevesMarco A Romano-SilvaHumberto Correa

Published in: Revista brasileira de psiquiatria (Sao Paulo, Brazil : 1999) (2023)

Further investigation is needed to improve the accuracy of machine learning, as its predictive qualities could potentially be highly useful in determining histories and possible outcomes of high-risk psychiatric patients.

Keyphrases

bipolar disorder
machine learning
major depressive disorder
end stage renal disease
ejection fraction
newly diagnosed
artificial intelligence
depressive symptoms
big data
prognostic factors
peritoneal dialysis
mental health
patient reported outcomes
multiple sclerosis
deep learning
pet ct
brain injury