I have a set of EEG data from 80 sick patients, and I know the outcomes of 6 of these patients (i.e. if they survived or died). I have discovered multiple measures that can be extracted from the EEG data that can be used to classify these 6 patients.
I would like to test how effective each measure is in predicting the outcome of the other 74 patients (the outcomes are known by the research group, but not me) and to be able to compare these methods of prediction.
I understand that the patients have to be split into multiple groups to deal with the problem of multiple hypothesis testing, but how can I go about this? I know that I can use a Support Vector Classifier to classify the data, but how does that account for multiple hypothesis testing? Does anyone have some resources or literature they can recommend on this topic?