Fuzzy set theory in medical diagnosis
IEEE Transactions on Systems, Man and Cybernetics
A self-learning expert system for diagnosis in traditional Chinese medicine
Expert Systems with Applications: An International Journal
Machine learning for medical diagnosis: history, state of the art and perspective
Artificial Intelligence in Medicine
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Medical diagnostic procedures generally comprise a step of collecting patients' symptoms, a step of diagnostic decisions, and a step of selecting appropriate methods of treatment. In traditional medical treatment based on analogical inference, analyzing present collected symptoms and choosing symptoms to query are mightily important for the diagnosis and these are essential conditions for appropriate treatment. Use of information systems that support present diversity of symptoms information and considerable options for the next step can avoid missing out timely and useful knowledge during the procedures. We have developed an application that having user interfaces guiding various analytic cases and their next optional choice and clinicians are able to improve the efficiency of procedures with this. By analyzing semantically linked data to symptoms, the application is possible to support efficiently collecting symptoms and selecting methods of treatment. This interfaces help users by requiring a minimal operation but supporting diverse probabilities.