IEEE Computational Intelligence Magazine - August 2018 - 27

2) Would augmenting social, demographic, and clinical data
[ S: C ] with metabolomics and genomics data improve the
prediction accuracies of treatment outcomes over using
only social, demographic, and clinical data 6S :C@ as predictor variables?
3) If the predictions improved as a result of augmenting
existing clinical measures with biological measures, how
many of the top predictors were biological measures?
Feature Selection and Choice of Classifiers

Three classes of classifiers are used in this work, including kernel, linear, and ensemble methods. For predicting outcomes
using baseline clinical, social, demographic, and metabolomic
data, we used support vector machines with linear kernels
(SVMLinear) and support vector machines that use radial-basis
kernels (SVM-RBF) as kernel methods [44]; a generalized linear model (GLM) as a linear method [45]; and GBMs as an
ensemble method [46]. As the creators of those methods have
indicated, each of those broader types has its own merits, mathematical nuances, and complexities, and all of them have been
used in other classification applications, such as in Kaggle [47].
To use all of the omics and clinical, social, and demographics
data to predict outcomes, we used nonparametric classifiers
such as SVM-RBF and random forests, as they are better suited
to handling correlated features [48], and have been used in predicting treatment outcomes in other psychiatric diseases such
as schizophrenia.

In addition to elastic-net regularization, recursive feature
elimination (i.e., a wrapper method) was also used for the
GLM and GBM classifiers; that made it possible to estimate the
model performance not only by optimizing the parameters of
the model, but also by searching for the right set of predictor
variables. Based on our datasets, the prediction performance did
not significantly vary with or without the use of any of the feature selection methods; the prediction accuracy remained
within 4%. This observation could also be in part due to a reasonably small size of predictor variables.
To minimize the effects of overfit and information leak,
nested cross-validation (nested-CV) with 5 repeats was used to
train the classifiers. In each repeat, data were randomized, and
the nested-CV comprised an outer loop and an inner loop. The
outer loop had a fivefold cross-validation to split the data into
training data (80% of the data) and testing data (the remaining
20%). The inner loop used the training data to train the classifier by using a tenfold cross-validation, and the trained classifier
was tested on the testing data. To minimize the effects of class
imbalance (i.e., unequal numbers of responders (60%) and nonresponders (40%)) in the training data, we used the synthetic
minority over-sampling (SMOTE) algorithm [49], which simulated patient profiles of the under-sampled class and up-sampled the under-sampled class to ensure that the two classes had
equal sizes. Prediction performance was reported using several
metrics (AUC, sensitivity, and specificity), and the statistical significance of the classifier's accuracy was established using the

Clinical Assessments
Depression Severity,
Social and Demographic Data,
Patient History

Predictive Models

Accuracy

Improvement?

Metebolomics

Genomics

Predictive Models

Predictive Models

Accuracy

Improvement?

Accuracy

FiguRE 4 the proposed analyses to establish improved predictability in antidepressant treatment outcomes by augmenting the clinicians'
assessments with biological measures.

auguSt 2018 | IEEE ComputatIonal IntEllIgEnCE magazInE

27



Table of Contents for the Digital Edition of IEEE Computational Intelligence Magazine - August 2018

Contents
IEEE Computational Intelligence Magazine - August 2018 - Cover1
IEEE Computational Intelligence Magazine - August 2018 - Cover2
IEEE Computational Intelligence Magazine - August 2018 - Contents
IEEE Computational Intelligence Magazine - August 2018 - 2
IEEE Computational Intelligence Magazine - August 2018 - 3
IEEE Computational Intelligence Magazine - August 2018 - 4
IEEE Computational Intelligence Magazine - August 2018 - 5
IEEE Computational Intelligence Magazine - August 2018 - 6
IEEE Computational Intelligence Magazine - August 2018 - 7
IEEE Computational Intelligence Magazine - August 2018 - 8
IEEE Computational Intelligence Magazine - August 2018 - 9
IEEE Computational Intelligence Magazine - August 2018 - 10
IEEE Computational Intelligence Magazine - August 2018 - 11
IEEE Computational Intelligence Magazine - August 2018 - 12
IEEE Computational Intelligence Magazine - August 2018 - 13
IEEE Computational Intelligence Magazine - August 2018 - 14
IEEE Computational Intelligence Magazine - August 2018 - 15
IEEE Computational Intelligence Magazine - August 2018 - 16
IEEE Computational Intelligence Magazine - August 2018 - 17
IEEE Computational Intelligence Magazine - August 2018 - 18
IEEE Computational Intelligence Magazine - August 2018 - 19
IEEE Computational Intelligence Magazine - August 2018 - 20
IEEE Computational Intelligence Magazine - August 2018 - 21
IEEE Computational Intelligence Magazine - August 2018 - 22
IEEE Computational Intelligence Magazine - August 2018 - 23
IEEE Computational Intelligence Magazine - August 2018 - 24
IEEE Computational Intelligence Magazine - August 2018 - 25
IEEE Computational Intelligence Magazine - August 2018 - 26
IEEE Computational Intelligence Magazine - August 2018 - 27
IEEE Computational Intelligence Magazine - August 2018 - 28
IEEE Computational Intelligence Magazine - August 2018 - 29
IEEE Computational Intelligence Magazine - August 2018 - 30
IEEE Computational Intelligence Magazine - August 2018 - 31
IEEE Computational Intelligence Magazine - August 2018 - 32
IEEE Computational Intelligence Magazine - August 2018 - 33
IEEE Computational Intelligence Magazine - August 2018 - 34
IEEE Computational Intelligence Magazine - August 2018 - 35
IEEE Computational Intelligence Magazine - August 2018 - 36
IEEE Computational Intelligence Magazine - August 2018 - 37
IEEE Computational Intelligence Magazine - August 2018 - 38
IEEE Computational Intelligence Magazine - August 2018 - 39
IEEE Computational Intelligence Magazine - August 2018 - 40
IEEE Computational Intelligence Magazine - August 2018 - 41
IEEE Computational Intelligence Magazine - August 2018 - 42
IEEE Computational Intelligence Magazine - August 2018 - 43
IEEE Computational Intelligence Magazine - August 2018 - 44
IEEE Computational Intelligence Magazine - August 2018 - 45
IEEE Computational Intelligence Magazine - August 2018 - 46
IEEE Computational Intelligence Magazine - August 2018 - 47
IEEE Computational Intelligence Magazine - August 2018 - 48
IEEE Computational Intelligence Magazine - August 2018 - 49
IEEE Computational Intelligence Magazine - August 2018 - 50
IEEE Computational Intelligence Magazine - August 2018 - 51
IEEE Computational Intelligence Magazine - August 2018 - 52
IEEE Computational Intelligence Magazine - August 2018 - 53
IEEE Computational Intelligence Magazine - August 2018 - 54
IEEE Computational Intelligence Magazine - August 2018 - 55
IEEE Computational Intelligence Magazine - August 2018 - 56
IEEE Computational Intelligence Magazine - August 2018 - 57
IEEE Computational Intelligence Magazine - August 2018 - 58
IEEE Computational Intelligence Magazine - August 2018 - 59
IEEE Computational Intelligence Magazine - August 2018 - 60
IEEE Computational Intelligence Magazine - August 2018 - 61
IEEE Computational Intelligence Magazine - August 2018 - 62
IEEE Computational Intelligence Magazine - August 2018 - 63
IEEE Computational Intelligence Magazine - August 2018 - 64
IEEE Computational Intelligence Magazine - August 2018 - 65
IEEE Computational Intelligence Magazine - August 2018 - 66
IEEE Computational Intelligence Magazine - August 2018 - 67
IEEE Computational Intelligence Magazine - August 2018 - 68
IEEE Computational Intelligence Magazine - August 2018 - 69
IEEE Computational Intelligence Magazine - August 2018 - 70
IEEE Computational Intelligence Magazine - August 2018 - 71
IEEE Computational Intelligence Magazine - August 2018 - 72
IEEE Computational Intelligence Magazine - August 2018 - 73
IEEE Computational Intelligence Magazine - August 2018 - 74
IEEE Computational Intelligence Magazine - August 2018 - 75
IEEE Computational Intelligence Magazine - August 2018 - 76
IEEE Computational Intelligence Magazine - August 2018 - Cover3
IEEE Computational Intelligence Magazine - August 2018 - Cover4
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202311
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202308
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202305
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202302
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202211
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202208
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202205
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202202
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202111
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202108
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202105
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202102
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202011
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202008
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202005
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202002
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201911
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201908
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201905
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201902
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201811
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201808
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201805
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201802
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter12
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall12
https://www.nxtbookmedia.com