AIMC Topic: Depressive Disorder, Major
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Cross-trial prediction of treatment outcome in depression: a machine learning approach.
The lancet. Psychiatry
Jan 21, 2016
BACKGROUND: Antidepressant treatment efficacy is low, but might be improved by matching patients to interventions. At present, clinicians have no empirically validated mechanisms to assess whether a patient with depression will respond to a specific ...
Studying depression using imaging and machine learning methods.
NeuroImage. Clinical
Nov 10, 2015
Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the ...
Analyzing depression tendency of web posts using an event-driven depression tendency warning model.
Artificial intelligence in medicine
Nov 2, 2015
OBJECTIVE: The Internet has become a platform to express individual moods/feelings of daily life, where authors share their thoughts in web blogs, micro-blogs, forums, bulletin board systems or other media. In this work, we investigate text-mining te...
Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.
Psychiatry research
Jul 5, 2015
Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict individual vulnerability to major depression (MD). Here, we use machine learning for the first time to ad...
Echo-Planar Imaging
Machine Learning
Guilt
Algorithms
Image Interpretation, Computer-Assisted
Nerve Net
Temporal Lobe
Case-Control Studies
Diagnosis, Computer-Assisted
Magnetic Resonance Imaging
Reference Values
Adult
Humans
Sensitivity and Specificity
Male
Depressive Disorder, Major
Biomarkers
Female
PsyGeNET: a knowledge platform on psychiatric disorders and their genes.
Bioinformatics (Oxford, England)
May 11, 2015
UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data...
Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.
Clinical EEG and neuroscience
Apr 14, 2014
Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an optimized classification method was tested in 147 patients with major depressive disorder (MDD) tre...
Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis.
Neuroscience and biobehavioral reviews
Jul 1, 2025
Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reduc...
Neuroimaging pattern interactions for suicide risk in depression captured by ensemble learning over transcriptome-defined parcellation.
Progress in neuro-psychopharmacology & biological psychiatry
Jun 20, 2025
BACKGROUND: For suicide in major depression disorder, it is urgent to seek for a reliable neuroimaging biomarker with interpretable links to molecular tissue signatures. Accordingly, we developed an ensemble learning scheme over transcriptome-defined...
Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.
Journal of affective disorders
Jun 15, 2025
BACKGROUND: Early diagnosis and treatment of mental illnesses is hampered by the lack of reliable markers. This study used machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder...
Comprehensive Characterization of Antidepressant Pharmacogenetics: A Systematic Review of Studies in Major Depressive Disorder.
Clinical and translational science
Jun 1, 2025
Pharmacogenetics is a promising strategy to facilitate individualized care for patients with Major Depressive Disorder (MDD). Research is ongoing to identify the optimal genetic markers for predicting outcomes to antidepressant therapies. The primary...
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