The paper is well written and describes an interesting and relatively novel approach to solving multi-class classification in a clinical domain where overlap between classes is frequently a possibility	['pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro', 'pro']	paper quality