Psychiatry Advisor

Accuracy of Machine Learning in Predicting CVD Risk in Bipolar Disease

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
New Atlas

Fitbit data accurately predicts bipolar disorder mood swings

Researchers have used Fitbit data to train a machine learning algorithm to accurately predict mood swings associated with bipolar disorder. It opens the door to using a personalized algorithm to drive ...
Healio

Machine learning models help to predict progression to schizophrenia, bipolar disorder

Please provide your email address to receive an email when new articles are posted on . The best model for predicting schizophrenia performed substantially better than the best bipolar ...
Science Daily

Researchers use fitness tracker data and machine learning to detect bipolar disorder mood swings

Investigators evaluated whether data collected from a fitness tracker could be used to accurately detect mood episodes in people with bipolar disorder. Study indicates that a fitness tracker can ...
EurekAlert!

Brigham researchers use fitness tracker data and machine learning to detect bipolar disorder mood swings

Study indicates that a fitness tracker can detect mood episodes in bipolar disorder to help drive treatment Investigators from Brigham and Women’s Hospital, a founding member of the Mass General ...