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Machine learning in major depression: From classification to treatment outcome prediction
Aims Major depression disorder (MDD) is the single greatest cause of disability and
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
morbidity, and affects about 10% of the population worldwide. Currently, there are no …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
Support vector machine
In this chapter, we explore Support Vector Machine (SVM)—a machine learning method that
has become exceedingly popular for neuroimaging analysis in recent years. Because of …
has become exceedingly popular for neuroimaging analysis in recent years. Because of …
Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification
Resting-state functional magnetic resonance imaging (rs-fMRI) data have been widely used
for automated diagnosis of brain disorders such as major depressive disorder (MDD) to …
for automated diagnosis of brain disorders such as major depressive disorder (MDD) to …
An insight into diagnosis of depression using machine learning techniques: a systematic review
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …
from which millions of individuals are affected today. The symptoms of depression are …
Review of EEG, ERP, and brain connectivity estimators as predictive biomarkers of social anxiety disorder
Social anxiety disorder (SAD) is characterized by a fear of negative evaluation, negative self-
belief and extreme avoidance of social situations. These recurrent symptoms are thought to …
belief and extreme avoidance of social situations. These recurrent symptoms are thought to …
Machine learning studies on major brain diseases: 5-year trends of 2014–2018
Abstract In the recent 5 years (2014–2018), there has been growing interest in the use of
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …
Spatio‐temporal graph convolutional network for diagnosis and treatment response prediction of major depressive disorder from functional connectivity
Y Kong, S Gao, Y Yue, Z Hou, H Shu, C ** a machine learning-based approach which could provide
quantitative identification of major depressive disorder (MDD) is essential for the diagnosis …
quantitative identification of major depressive disorder (MDD) is essential for the diagnosis …