Psychiatry

Bipolar Disorder

Latest AI and machine learning research in bipolar disorder for healthcare professionals.

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Towards a brain-based predictome of mental illness.

Neuroimaging-based approaches have been extensively applied to study mental illness in recent years ...

Machine-learning models for depression and anxiety in individuals with immune-mediated inflammatory disease.

OBJECTIVE: Individuals with immune-mediated inflammatory disease (IMID) have a higher prevalence of ...

Noise can speed backpropagation learning and deep bidirectional pretraining.

We show that the backpropagation algorithm is a special case of the generalized Expectation-Maximiza...

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

OBJECTIVES: The existence of anatomofunctional brain abnormalities in bipolar disorder (BD) is now w...

The Virtual Operative Assistant: An explainable artificial intelligence tool for simulation-based training in surgery and medicine.

Simulation-based training is increasingly being used for assessment and training of psychomotor skil...

A proof of concept machine learning analysis using multimodal neuroimaging and neurocognitive measures as predictive biomarker in bipolar disorder.

BACKGROUND: Concomitant use of complementary, multimodal imaging measures and neurocognitive measure...

Development of an early-warning system for high-risk patients for suicide attempt using deep learning and electronic health records.

Suicide is the tenth leading cause of death in the United States (US). An early-warning system (EWS)...

Predicting individual clinical trajectories of depression with generative embedding.

Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly varia...

Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia.

IMPORTANCE: Little guidance exists to date on how to select antipsychotic medications for patients w...

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases....

Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database.

INTRODUCTION: Major depressive disorder (MDD) is one of the most common mental disorders worldwide. ...

Ensemble Learning for Early-Response Prediction of Antidepressant Treatment in Major Depressive Disorder.

BACKGROUND: In order to reduce unsuccessful treatment trials for depression, neuroimaging and geneti...

Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry.

Depression or Major Depressive Disorder (MDD) is a mental illness which negatively affects how a per...

Developing algorithms to predict adult onset internalizing disorders: An ensemble learning approach.

A growing literature is utilizing machine learning methods to develop psychopathology risk algorithm...

Prediction of lithium response using clinical data.

OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patient...

Implementing machine learning in bipolar diagnosis in China.

Bipolar disorder (BPD) is often confused with major depression, and current diagnostic questionnaire...

Predicting rehospitalization within 2 years of initial patient admission for a major depressive episode: a multimodal machine learning approach.

Machine learning methods show promise to translate univariate biomarker findings into clinically use...

ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder.

Treating patients with major depressive disorder is challenging because it takes several months for ...

A network perspective on body dysmorphic disorder and major depressive disorder.

BACKGROUND: Body dysmorphic disorder (BDD) is a highly debilitating mental disorder associated with ...

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