Abstract
Medical diagnosis is a classical example of approximate reasoning, and also one of the earliest applications of expert systems. The existing approaches to approximate reasoning in medical diagnosis are mainly based on Probability Theory and/or Multivalued Logic. Unfortunately, most of these approaches have not been able to model medical diagnostic reasoning sufficiently, or in a clinically intuitive way. The model described in this paper attempts to overcome the main limitations of the existing approaches.
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Fernando, I., Henskens, F., Cohen, M. (2013). An Approximate Reasoning Model for Medical Diagnosis. In: Lee, R. (eds) Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing. Studies in Computational Intelligence, vol 492. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00738-0_2
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DOI: https://doi.org/10.1007/978-3-319-00738-0_2
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