What are some data mining techniques for analyzing cause of disease

I have a dataset of 300 observations, of which 200 are normal, and the rest have the disease. I have the cognitive assessment scores of these 300 participants, and the assessment is divided into different sections: delusions, depression, anxiety, etc. I'm wondering what technique(s) would be good to look at the variation within the data. And whether a certain section's score would be a good predictor of the participant having the disease. I know of logistic regression, and with that I can construct a classification tree and an ROC curve. Are there any other techniques that I can use here? I'm open to different approaches (techniques for predicting, or just any other ways to look at the data in a meaningful way).


Active Member
Try also Nearest Neighbor and Linear Discriminant Analysis (LDA). More complex techniques (data mining) are not applicable on such a small data set.