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Recent Developments and the New Direction in Soft-Computing Foundations and Applications pp 549–557Cite as

Fuzzy Logic Based Simulation of Gynaecology Disease Diagnosis

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Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 361))

Abstract

The first step in a knowledge base expert system could be to mathematically evaluate perceptions of the domain experts which are invariably expressed in linguistic terms based on their tactic knowledge followed by the defined steps in differential diagnostic process. We have simulated the process in three stages, especially in gynaecological diseases. Stage I, refers to Type1 Fuzzy Relational Calculus used to arrive at the initial diagnostic labels for gynaecological diseases in patients and to estimate similarity between the domain experts. The case study focused only on the identified gynaecological diseases arrives at comparatively low diagnostic percentage, and therefore termed as Initial Screening Process. The output of the algorithm for patient diagnostic records, considering the variability among the experts, was tested for diagnosing a single disease. After application of ‘History’ fuzzy rule base in Stage 2, using Type 1 Fuzzy Inference System, the accuracy was increased to some extent which was further enhanced to high level by Stage III for the prototype of 226 patients diagnosed by the model. The need based research presented will ultimately assist physicians and upcoming gynaecologists.

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References

  1. A. Mahdi, A. Razali, Al. Alwakil, Comparison of fuzzy diagnosis with K-nearest neighbor and Naïve Bayes classifiers in disease diagnosis. Broad Res. Artif. Intell. Neurosci. 2 (2011). ISSN 2067-3957(online), ISSN 2068-0473(print)

    Google Scholar 

  2. A.R. Meenakshi, M. Kaliraja, An application of interval valued fuzzy matrices in medical diagnosis. Int. J. Math. Anal. 5, 2792–2803 (2011)

    MathSciNet  MATH  Google Scholar 

  3. E. Sanchez, Inverse of fuzzy relations, application to possibility distributions and medical diagnosis. Fuzzy Sets Syst. 2(1) (1979)

    Article  MathSciNet  Google Scholar 

  4. F. Steimann, Fuzzy set theory in medicine. Artif. Intell. Med. 11, 1–7 (1997)

    Google Scholar 

  5. L.I. Kuncheva, F. Steimann, Fuzzy Diagnosis. Artif. Intell. Med. 16, 121–128 (1999)

    Article  Google Scholar 

  6. M.A.M. Reis, N.R.S. Ortega, P.S.P. Silveira, Fuzzy expert system in prediction of neonatal rescuscitation. Braz. J. Med. Biol. Res. 37(2) (2004)

    Google Scholar 

  7. P.R. Innocent, R.I. John, Computer aided fuzzy medical diagnosis. Inf. Sci. 162, 81–104 (2004)

    Article  Google Scholar 

  8. G.J. Klir, C. Bo Yuan, Fuzzy Sets and Fuzzy Logic, Theory and Applications (Prentice Hall P.T.R., Upper Saddle River, New Jersey, 1995)

    Google Scholar 

  9. T. Ross, Fuzzy Logic with Engineering Applications (Wiley, Chichester, 2010)

    Book  Google Scholar 

  10. A. Sardesai, V. Khrat, A. Deshpande, P. Sambarey, Fuzzy logic based formalisms for gynaecology disease diagnosis. J. Intell. Syst. (2016). https://doi.org/10.1515/jisys-2015-0106

  11. A. Sardesai, V. Khrat, A. Deshpande, P. Sambarey, Initial screening of gynecological diseases in a patient, expert’s knowledgebase and fuzzy set theory: a case study in India, in Proceedings of the 2nd World Conference on Soft Computing, Baku, Azerbaijan (2012), pp. 258–262

    Google Scholar 

  12. A. Sardesai, V. Kharat, A.W. Deshpande, P.W. Sambarey, Efficacy of fuzzy-stat modelling in classification of gynaecologists and patients. J. Intell. Syst. (2015). https://doi.org/10.1515/jisys-2015-0001

  13. A. Sardesai, V. Khrat, A. Deshpande, P. Sambarey, Fuzzy logic application in gynaecology: a case study, in Proceedings of the 3rd International Conference on Informatics, Electronics and Vision 2014, Dhaka, Bangladesh, IEEE explore digital library (2014)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science, Modern College of Arts, Science and Commerce, Shivajinagar, Pune, 411005, India

    A. S. Sardesai

  2. Department of Mathematics, Savitribai Phule Pune University, Ganeshkhind, Pune, 411007, Maharashtra, India

    V. S. Kharat

  3. Berkeley Initiative in Soft Computing (BISC)-SIG-EMS, University of California, Berkeley, California, United States of America

    A. W. Deshpande

  4. Department of Gynaecology, B. J. Medical College, Pune, India

    P. W. Sambarey

Authors
  1. A. S. Sardesai
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  2. V. S. Kharat
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  3. A. W. Deshpande
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  4. P. W. Sambarey
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Corresponding author

Correspondence to A. S. Sardesai .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA

    Lotfi A. Zadeh

  2. Machine Intelligence Institute, Iona College, New Rochelle, New York, USA

    Ronald R. Yager

  3. Department of Information Technology and Programming, Azerbaijan Technical University, Baku, Azerbaijan

    Shahnaz N. Shahbazova

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta, Canada

    Marek Z. Reformat

  5. Department of Computer Science, University of Texas at El Paso, El Paso, Texas, USA

    Vladik Kreinovich

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Sardesai, A.S., Kharat, V.S., Deshpande, A.W., Sambarey, P.W. (2018). Fuzzy Logic Based Simulation of Gynaecology Disease Diagnosis. In: Zadeh, L., Yager, R., Shahbazova, S., Reformat, M., Kreinovich, V. (eds) Recent Developments and the New Direction in Soft-Computing Foundations and Applications. Studies in Fuzziness and Soft Computing, vol 361. Springer, Cham. https://doi.org/10.1007/978-3-319-75408-6_42

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  • DOI: https://doi.org/10.1007/978-3-319-75408-6_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75407-9

  • Online ISBN: 978-3-319-75408-6

  • eBook Packages: EngineeringEngineering (R0)

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