Machine learning in major depression: From classification to treatment outcome prediction
S Gao, VD Calhoun, J Sui - CNS neuroscience & therapeutics, 2018 - Wiley Online Library
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 …
Bipolar disorder diagnosis: challenges and future directions
ML Phillips, DJ Kupfer - The Lancet, 2013 - thelancet.com
Bipolar disorder refers to a group of affective disorders, which together are characterised by
depressive and manic or hypomanic episodes. These disorders include: bipolar disorder …
depressive and manic or hypomanic episodes. These disorders include: bipolar disorder …
Using support vector machine to identify imaging biomarkers of neurological and psychiatric disease: a critical review
G Orru, W Pettersson-Yeo, AF Marquand… - Neuroscience & …, 2012 - Elsevier
Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical
and functional differences between healthy individuals and patients suffering a wide range …
and functional differences between healthy individuals and patients suffering a wide range …
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 …
[HTML][HTML] From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics
Psychiatric disorders are increasingly being recognised as having a biological basis, but
their diagnosis is made exclusively behaviourally. A promising approach for …
their diagnosis is made exclusively behaviourally. A promising approach for …
Emotional valence modulates brain functional abnormalities in depression: evidence from a meta-analysis of fMRI studies
NA Groenewold, EM Opmeer, P de Jonge… - Neuroscience & …, 2013 - Elsevier
Models describing the neural correlates of biased emotion processing in depression have
focused on increased activation of anterior cingulate and amygdala and decreased …
focused on increased activation of anterior cingulate and amygdala and decreased …
Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma
Objective The status of isocitrate dehydrogenase 1 (IDH1) is highly correlated with the
development, treatment and prognosis of glioma. We explored a noninvasive method to …
development, treatment and prognosis of glioma. We explored a noninvasive method to …
[图书][B] Conformal prediction for reliable machine learning: theory, adaptations and applications
The conformal predictions framework is a recent development in machine learning that can
associate a reliable measure of confidence with a prediction in any real-world pattern …
associate a reliable measure of confidence with a prediction in any real-world pattern …
Confusion-matrix-based kernel logistic regression for imbalanced data classification
M Ohsaki, P Wang, K Matsuda… - … on Knowledge and …, 2017 - ieeexplore.ieee.org
There have been many attempts to classify imbalanced data, since this classification is
critical in a wide variety of applications related to the detection of anomalies, failures, and …
critical in a wide variety of applications related to the detection of anomalies, failures, and …
Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and …
CHY Fu, H Steiner, SG Costafreda - Neurobiology of disease, 2013 - Elsevier
We performed a systematic review and meta-analysis of neural predictors of response to the
most commonly used, evidence based treatments in clinical practice, namely …
most commonly used, evidence based treatments in clinical practice, namely …