A Method for Automatic Medical Diagnosis
AbstractThis research paper presents a new method for the automatic diagnosis of diseases using a personal computer. Forming a basis for the characterization of diseases, a wide set of symptoms is introduced, and a particular disease is characterized by a set of statistical weights assigned to those symptoms. Information about the patient’s state is provided by a graphic interface in which the user confirms symptom indicators. Agreement between these symptoms and classified symptoms of a particular disease is then estimated by the sum of corresponding weights, where the disease corresponding to the maximal agreement is proposed as the result of the diagnosis. A disease likelihood estimator is calculated and presented to assess the reliability of the diagnosis. With regard to the automatic assessment of the diagnosis the corresponding algorithm and the properties of the computer program are included. Finally, the effectiveness of this method of medical diagnosis is demonstrated through four typical examples involving differently expressed symptoms. The diagnostic system resembles semantically driven sensory-neural network.
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M. Sok, E. Švegl, and I. Grabec, Sensory-neural Network for Medical Diagnosis, Evolving and Adaptive Intelligent Systems EAIS 2017, May 31 June 2, 2017, Ljubljana, Slovenia, http://msc.fe.uni-lj.si/eais2017, Publisher: https://www.ieee.org
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