Since diagnostic errors can lead to severe consequences for a patient, medical schools are searching for advanced methodologies to teach and asses diagnostic reasoning. Computer software or actors portraying patients are used to present the symptoms of a disease to the students, and the students' approach in diagnosing that disease are recorded. An expert analyzes that record to classify each approach as being correct or incorrect and then recommends appropriate training for each student. With the goal of automating this classification process, neural network-based supervised algorithms are tested in this investigation. The task here is to reliably classify the diagnosis...