AIMC Topic: Depressive Disorder, Major

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Classifying Treated vs. Untreated MDD Adolescents from Anatomical Connectivity using Nonlinear SVM.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Identification of the treatment-related responders for adolescent Major Depressive Disorder (MDD) is urgently needed to develop effective treatments. In this paper, machine learning based classifiers are used to reveal anatomical features as responde...
Young Adult Male Brain Female Adolescent Support Vector Machine Diffusion Tensor Imaging Depressive Disorder, Major Case-Control Studies Humans
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Refining Prediction in Treatment-Resistant Depression: Results of Machine Learning Analyses in the TRD III Sample.

The Journal of clinical psychiatry Jan 1, 2018
OBJECTIVE: The study objective was to generate a prediction model for treatment-resistant depression (TRD) using machine learning featuring a large set of 47 clinical and sociodemographic predictors of treatment outcome.
Humans Female Adult Machine Learning Forecasting Models, Statistical Antidepressive Agents Depressive Disorder, Treatment-Resistant Depressive Disorder, Major Treatment Outcome Male Middle Aged
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Differential privacy-based evaporative cooling feature selection and classification with relief-F and random forests.

Bioinformatics (Oxford, England) Sep 15, 2017
MOTIVATION: Classification of individuals into disease or clinical categories from high-dimensional biological data with low prediction error is an important challenge of statistical learning in bioinformatics. Feature selection can improve classific...
Classification Models, Biological Privacy Machine Learning Software Depressive Disorder, Major Computational Biology Humans
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Prediction of Individual Response to Electroconvulsive Therapy via Machine Learning on Structural Magnetic Resonance Imaging Data.

JAMA psychiatry Jun 1, 2016
IMPORTANCE: Electroconvulsive therapy (ECT) is one of the most effective treatments for severe depression. However, biomarkers that accurately predict a response to ECT remain unidentified.
Electroconvulsive Therapy Antidepressive Agents Gyrus Cinguli Humans Depressive Disorder, Major Prospective Studies Treatment Outcome Biomarkers Machine Learning Predictive Value of Tests Male Magnetic Resonance Imaging Female Combined Modality Therapy Adult Middle Aged
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A clinical perspective on the relevance of research domain criteria in electronic health records.

The American journal of psychiatry Apr 1, 2015
OBJECTIVE: The limitations of the DSM nosology for capturing dimensionality and overlap in psychiatric syndromes, and its poor correspondence to underlying neurobiology, have been well established. The Research Domain Criteria (RDoC), a proposed dime...
Models, Psychological Patient Readmission Reproducibility of Results Schizophrenic Psychology Electronic Health Records Risk Factors Depressive Disorder, Major Female Schizophrenia Humans Hospitalization Information Storage and Retrieval Length of Stay Adult Psychotic Disorders Mental Disorders Cohort Studies Male Natural Language Processing Middle Aged
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