A Method for Automatic Medical Diagnosis

  • Igor Grabec Amanova Ltd, Technology park of Ljubljana
  • Eva Švegl Faculty of Medicine, University of Ljubljana, SI-1000 Ljubljana, Slovenia
  • Mihael Sok University Medical Center, SI-1000 Ljubljana, Slovenia
Keywords: Automatic Statistical Diagnosis, Non-parametric Inference, Disease Likelihood


This 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.

Author Biographies

Igor Grabec, Amanova Ltd, Technology park of Ljubljana
Academitian, Emeritus Professor, University of ljubljana
Eva Švegl, Faculty of Medicine, University of Ljubljana, SI-1000 Ljubljana, Slovenia
Mihael Sok, University Medical Center, SI-1000 Ljubljana, Slovenia
Univ. Professor


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How to Cite
Grabec, I., Švegl, E., & Sok, M. (2019). A Method for Automatic Medical Diagnosis. Statistics, Optimization & Information Computing, 7(1), 26-39. https://doi.org/10.19139/soic.v7i1.414
Research Articles