Accurate classification of depression through optimized machine learning models on high-dimensional noisy data

[1]  Tim P. Moran,et al.  The psychometric properties of the late positive potential during emotion processing and regulation , 2013, Brain Research.

[2]  Greg H. Proudfit,et al.  Depression and Event-related Potentials: Emotional disengagement and reward insensitivity. , 2015, Current opinion in psychology.

[3]  Jianyu Long,et al.  A comparison of dimension reduction techniques for support vector machine modeling of multi-parameter manufacturing quality prediction , 2019, J. Intell. Manuf..

[4]  Dan Foti,et al.  Reduced electrocortical response to threatening faces in major depressive disorder , 2010, Depression and anxiety.

[5]  Wen-hua Liu,et al.  The influence of anhedonia on feedback negativity in major depressive disorder , 2014, Neuropsychologia.

[6]  Aamir Saeed Malik,et al.  A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD) , 2018, Medical & Biological Engineering & Computing.

[7]  E. Walker,et al.  Diagnostic and Statistical Manual of Mental Disorders , 2013 .

[8]  J. Friedman.  Greedy function approximation: A gradient boosting machine. , 2001 .

[9]  Sanchita Paul,et al.  Detection of major depressive disorder using linear and non-linear features from EEG signals , 2018, Microsystem Technologies.

[10]  Tianqi Chen,et al.  XGBoost: A Scalable Tree Boosting System , 2016, KDD.

[11]  R. Kotov,et al.  Blunted Neural Response to Rewards as a Prospective Predictor of the Development of Depression in Adolescent Girls. , 2016, The American journal of psychiatry.

[12]  Age K. Smilde,et al.  Principal Component Analysis , 2003, Encyclopedia of Machine Learning.

[13]  Ahmad Khodayari-Rostamabad,et al.  A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder , 2013, Clinical Neurophysiology.

[14]  P. Rossini,et al.  Neurophysiological assessment of Alzheimer's disease individuals by a single electroencephalographic marker. , 2015, Journal of Alzheimer's disease : JAD.

[15]  Zachary P. Infantolino,et al.  Reliability of the electrocortical response to gains and losses in the doors task. , 2017, Psychophysiology.

[16]  Alexander M. Nitsch,et al.  A Single-Trial Estimation of the Feedback-Related Negativity and Its Relation to BOLD Responses in a Time-Estimation Task , 2014, The Journal of Neuroscience.

[17]  Dan Foti,et al.  Reward dysfunction in major depression: Multimodal neuroimaging evidence for refining the melancholic phenotype , 2014, NeuroImage.

[18]  H. Adeli,et al.  Fractality analysis of frontal brain in major depressive disorder. , 2012, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[19]  G. Hajcak,et al.  Reduced neural response to reward and pleasant pictures independently relate to depression , 2020, Psychological Medicine.

[20]  G. Hajcak,et al.  Neural Response to Pleasant Pictures Moderates Prospective Relationship Between Stress and Depressive Symptoms in Adolescent Girls , 2019, Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53.

[21]  N. Altman.  An Introduction to Kernel and Nearest-Neighbor Nonparametric Regression , 1992 .

[22]  G. Hajcak,et al.  Using Multilevel Modeling to Examine Blunted Neural Responses to Reward in Major Depression. , 2018, Biological psychiatry. Cognitive neuroscience and neuroimaging.

[23]  Greg Hajcak,et al.  The Utility of Event-Related Potentials in Clinical Psychology. , 2019, Annual review of clinical psychology.

[24]  David H. Wolpert,et al.  Stacked generalization , 1992, Neural Networks.

[25]  R. Kotov,et al.  Depression and reduced neural response to emotional images: Distinction from anxiety, and importance of symptom dimensions and age of onset. , 2016, Journal of abnormal psychology.

[26]  Vladimir Vapnik,et al.  Support-vector networks , 2004, Machine Learning.

[27]  Reza Rostami,et al.  Classifying depression patients and normal subjects using machine learning techniques , 2011, 2011 19th Iranian Conference on Electrical Engineering.

[28]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[29]  Aamir Saeed Malik,et al.  Electroencephalogram (EEG)-based computer-aided technique to diagnose major depressive disorder (MDD) , 2017, Biomed. Signal Process. Control..

[30]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[31]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[32]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[33]  Aamir Saeed Malik,et al.  Review on EEG and ERP predictive biomarkers for major depressive disorder , 2015, Biomed. Signal Process. Control..

[34]  D. Barch,et al.  Preschool-Onset Major Depressive Disorder is Characterized by Electrocortical Deficits in Processing Pleasant Emotional Pictures , 2020, Journal of abnormal child psychology.

[35]  Pierre Geurts,et al.  Extremely randomized trees , 2006, Machine Learning.

[36]  R. Kotov,et al.  Diagnostic and Symptom-Based Predictors of Emotional Processing in Generalized Anxiety Disorder and Major Depressive Disorder: An Event-Related Potential Study , 2016, Cognitive Therapy and Research.

[37]  Farzana Anowar,et al.  Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE) , 2021, Comput. Sci. Rev..

[38]  G. Hajcak,et al.  Self-report and behavioral measures of reward sensitivity predict the feedback negativity. , 2013, Psychophysiology.

[39]  E. B. Wilson.  Probable Inference, the Law of Succession, and Statistical Inference , 1927 .

[40]  Jing Sui,et al.  Machine learning in major depression: From classification to treatment outcome prediction , 2018, CNS neuroscience & therapeutics.

[41]  C. Sylvester,et al.  Depression and Anxiety in Preschoolers: A Review of the Past 7 Years. , 2017, Child and adolescent psychiatric clinics of North America.

[42]  Lilianne R. Mujica-Parodi,et al.  Ventral striatal and medial prefrontal BOLD activation is correlated with reward-related electrocortical activity: A combined ERP and fMRI study , 2011, NeuroImage.

[43]  M. Bradley,et al.  Brain potentials in affective picture processing: covariation with autonomic arousal and affective report , 2000, Biological Psychology.