AIMC Topic: Antidepressive Agents
Clear Filters Showing 21 to 30 of 57 articles
Predicting Outcomes of Antidepressant Treatment in Community Practice Settings.
Psychiatric services (Washington, D.C.)
Dec 5, 2023
OBJECTIVE: The authors examined whether machine-learning models could be used to analyze data from electronic health records (EHRs) to predict patients' responses to antidepressant medications.
Treatment selection using prototyping in latent-space with application to depression treatment.
PloS one
Nov 12, 2021
Machine-assisted treatment selection commonly follows one of two paradigms: a fully personalized paradigm which ignores any possible clustering of patients; or a sub-grouping paradigm which ignores personal differences within the identified groups. W...
Replication of machine learning methods to predict treatment outcome with antidepressant medications in patients with major depressive disorder from STAR*D and CAN-BIND-1.
PloS one
Jun 28, 2021
OBJECTIVES: Antidepressants are first-line treatments for major depressive disorder (MDD), but 40-60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict trea...
Prediction of pharmacological activities from chemical structures with graph convolutional neural networks.
Scientific reports
Jan 12, 2021
Many therapeutic drugs are compounds that can be represented by simple chemical structures, which contain important determinants of affinity at the site of action. Recently, graph convolutional neural network (GCN) models have exhibited excellent res...
Precision psychiatry in clinical practice.
International journal of psychiatry in clinical practice
Aug 27, 2020
The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance criteria is an error-prone process. Recently, pharmacogenetic biomarkers entered in prescribing gui...
Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.
JAMA network open
Jun 1, 2020
IMPORTANCE: Despite the high prevalence and potential outcomes of major depressive disorder, whether and how patients will respond to antidepressant medications is not easily predicted.
Ensemble Learning for Early-Response Prediction of Antidepressant Treatment in Major Depressive Disorder.
Journal of magnetic resonance imaging : JMRI
Dec 20, 2019
BACKGROUND: In order to reduce unsuccessful treatment trials for depression, neuroimaging and genetic information can be considered as biomarkers. Together with machine-learning methods, prediction models have proved to be valuable for baseline predi...
Computational modeling of the monoaminergic neurotransmitter and male neuroendocrine systems in an analysis of therapeutic neuroadaptation to chronic antidepressant.
European neuropsychopharmacology : the journal of the European College of Neuropsychopharmacology
Dec 9, 2019
Second-line depression treatment involves augmentation with one (rarely two) additional drugs, of chronic administration of a selective serotonin reuptake inhibitor (SSRI), which is the first-line depression treatment. Unfortunately, many depressed p...
Predicting rehospitalization within 2 years of initial patient admission for a major depressive episode: a multimodal machine learning approach.
Translational psychiatry
Nov 11, 2019
Machine learning methods show promise to translate univariate biomarker findings into clinically useful multivariate decision support systems. At current, works in major depressive disorder have predominantly focused on neuroimaging and clinical pred...
ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder.
Genes
Nov 7, 2019
Treating patients with major depressive disorder is challenging because it takes several months for antidepressants prescribed for the patients to take effect. This limitation may result in increased risks and treatment costs. To address this limitat...
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