1. A Brief Example MRI data and metadata on PTSD patients
Hippocampal volume from structural MRI
Intracranial volume from structural MRI
NAA levels from MRSI
Age
Education Level
CAPS score (estimated PTSD severity based on psychological exam)

2. A Brief Example
I - Get Data Into Readable Format - WEKA recognizes quite a few – ARFF (primary), CSV…

4. A Brief Example
Open Weka…

8. A Brief Example
Explore the data…

16. A Brief Example
Based on exploring the data, some thoughts on a preliminary analysis
Reduce number of variables (there are also formal ways of “subset selection” – stepwise regression, criteria based (AIC), the lasso, pace regression,…)
“Disctretize” CAPS (as measure of PTSD severity) and try classifying on discretized CAPS score

17. A Brief Example
Select varible subset, discretize CAPS score in Weka and save result as an ARFF file

22. A Brief Example
Do some classifications in the Weka Epxplorer…

24. A Brief Example C 4.5 Decision Tree: Age Education <= 13 > 13
Rt Hipp Vol
Lt Hipp Vol
PTSD-
Age
PTSD+
Intracr Vol
>3.01
<= 13
> 13
<=3.01.
<=43
>43
<=2.66
>2.66
<=2.43
>2.43
<= 15
> 15
<= 1403
> 1403
<= 33
> 33

25. A Brief Example
Then can automate application of multiple algorithms on multiple data sets (e.g. discretization of CAPS scores into different numbers of bins) using the Weka Experimenter

27. A Brief Example
Results using Weka Experimenter (10 times, 10 fold corss validation) – prediction accuracy: