Predicting the naturalistic course in anxiety disorders using clinical and biological markers: a machine learning approach.

Wicher A BokmaPaul ZhutovskyErik J GiltayRobert A SchoeversBrenda W J H PenninxAnton L J M van BalkomNeeltje M BatelaanGuido A van Wingen

Published in: Psychological medicine (2020)

The current study showed moderate performance in predicting recovery from anxiety disorders over a 2-year follow-up for individual patients and indicates that anxiety features are most indicative for anxiety improvement and depression features for improvement in general.

Keyphrases

machine learning
end stage renal disease
sleep quality
newly diagnosed
chronic kidney disease
ejection fraction
prognostic factors
high intensity
artificial intelligence
patient reported outcomes