AI Medical Compendium Journal:
Bipolar disorders

Showing 1 to 6 of 6 articles

Predicting remission after acute phase pharmacotherapy in patients with bipolar I depression: A machine learning approach with cross-trial and cross-drug replication.

Bipolar disorders
OBJECTIVES: Interpatient variability in bipolar I depression (BP-D) symptoms challenges the ability to predict pharmacotherapeutic outcomes. A machine learning workflow was developed to predict remission after 8 weeks of pharmacotherapy (total score ...

Machine-based learning of multidimensional data in bipolar disorder - pilot results.

Bipolar disorders
INTRODUCTION: Owing to the heterogenic picture of bipolar disorder, it takes approximately 8.8 years to reach a correct diagnosis. Early recognition and early intervention might not only increase quality of life, but also increase life expectancy as ...

Comment on published article "A chat about bipolar disorder".

Bipolar disorders
To the Editor, we follow the topic "A chat about bipolar disorder ". According to the study's findings, ChatGPT proved its ability to deliver basic and informative information on bipolar disorders.

Will machine learning applied to neuroimaging in bipolar disorder help the clinician? A critical review and methodological suggestions.

Bipolar disorders
OBJECTIVES: The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now well established by magnetic resonance imaging (MRI) studies. To create diagnostic and prognostic tools, as well as identifying biologically valid subt...

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force.

Bipolar disorders
OBJECTIVES: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learnin...