AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Depressive Disorder, Major

Showing 141 to 150 of 190 articles

Clear Filters

Augmented outcome-weighted learning for estimating optimal dynamic treatment regimens.

Statistics in medicine
Dynamic treatment regimens (DTRs) are sequential treatment decisions tailored by patient's evolving features and intermediate outcomes at each treatment stage. Patient heterogeneity and the complexity and chronicity of many diseases call for learning...

A morphometric signature of depressive symptoms in unmedicated patients with mood disorders.

Acta psychiatrica Scandinavica
OBJECTIVE: A growing literature indicates that unipolar depression and bipolar depression are associated with alterations in grey matter volume. However, it is unclear to what degree these patterns of morphometric change reflect symptom dimensions. H...

Predicting individual responses to the electroconvulsive therapy with hippocampal subfield volumes in major depression disorder.

Scientific reports
Electroconvulsive therapy (ECT) is one of the most effective treatments for major depression disorder (MDD). ECT can induce neurogenesis and synaptogenesis in hippocampus, which contains distinct subfields, e.g., the cornu ammonis (CA) subfields, a g...

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder.

Journal of psychiatric research
Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be ...

Machine-Learning Classifier for Patients with Major Depressive Disorder: Multifeature Approach Based on a High-Order Minimum Spanning Tree Functional Brain Network.

Computational and mathematical methods in medicine
High-order functional connectivity networks are rich in time information that can reflect dynamic changes in functional connectivity between brain regions. Accordingly, such networks are widely used to classify brain diseases. However, traditional me...

Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features.

Neuroscience bulletin
Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian ...

Estimation and evaluation of linear individualized treatment rules to guarantee performance.

Biometrics
In clinical practice, an informative and practically useful treatment rule should be simple and transparent. However, because simple rules are likely to be far from optimal, effective methods to construct such rules must guarantee performance, in ter...

A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD).

Medical & biological engineering & computing
Major depressive disorder (MDD), a debilitating mental illness, could cause functional disabilities and could become a social problem. An accurate and early diagnosis for depression could become challenging. This paper proposed a machine learning fra...

Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder.

Psychiatry research. Neuroimaging
Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures ...

Diagnosis of major depressive disorder by combining multimodal information from heart rate dynamics and serum proteomics using machine-learning algorithm.

Progress in neuro-psychopharmacology & biological psychiatry
OBJECTIVE: Major depressive disorder (MDD) is a systemic and multifactorial disorder that involves abnormalities in multiple biochemical pathways and the autonomic nervous system. This study applied a machine-learning method to classify MDD and contr...