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A fuzzy approach for determination of prostate cancer

Year 2013, Volume: 1 Issue: 1, 1 - 7, 28.02.2013

İsmail Saritas Novruz Allahverdi İbrahim Sert

Abstract

Goal of this study is a design of a fuzzy expert system, its application aspects in the medicine area and its introduction for calculation of numeric value of prostate cancer risk. For this aim it was used prostate specific antigen (PSA), age and prostate volume (PV) as system input parameters and prostate cancer risk (PCR) as output. This system gives user a range of the risk of the cancer disease and facilitates the decision of the doctor if there is a need for the biopsy. The designed system was tested by the data from the literature and the clinical data. It was compared the diagnoses data of specialists of the every disease situation and literature data and it was seen that the system can be available for every situation. It is observed that this system is rapid because it needs minimum calculation, economical, without any risk than traditional diagnostic systems, has also a high reliability than the other system and can be used as assistant system for physicians. Having used in the hospital this system was tested as decision support system and the approach used in this study can be used in difference studies and analyses, because the system is transparent and explainable to a user. his is the abstract section.

Keywords

Fuzzy logic; fuzzy expert system; prostate cancer; prostate specific antigen; prostate cancer risk

References

  • Abbod MF, von Keyserlingk DG, Linkens DA (2001). Mahfouf M. Survey of utilization of fuzzy technology in medicine and healthcare. Fuzzy Sets and Systems. 120:331–349.
  • Allahverdi N (2001). Uzman Sistemler Bir Yapay Zeka Uygulaması. Nobel Yayıncılık. Ankara. 1-248.
  • Allahverdi N, Yaldız S (1998). Expert System Applications in Medicine and Example of Design of a Pre-Diagnosis Expert System. Proc. Second Turkish-German Joint Computer Application Days. 175-192.
  • Allahverdi N, Torun S, Saritas I (2007). Design of a fuzzy expert system for determination of coronary heart disease risk. International Conference on Computer Systems and Technologies-CompSysTech’07, June 2007, Rousse, Bulgaria. II.A: 14.1-14.8.
  • Boegla K, Adlassniga KP, Hayashic Y, Rothenfluhd TE, Leiticha H (2002). Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System. Artificial Intelligence in Medicine. Vol. 676 : 1–26.
  • Brawer MK, Kirby R (1999). Prostate Specific Antigen. In: Brawer MK, Kirby R, eds. Prostate Spesific Antigen. 2nd ed. Health Press. 1-96.
  • Cancer Risk Calculator (2012). Forecasting the risk of disease, http://www.compass. fhcrc.org/edrnnci/bin/calculator/.
  • Kaiser Permanente (2006). Healty manager, http://www.kaiserpermanente.org /medicine/.
  • Lorenz A, Blum M, Ermert H, Senge T (2007). Comparison of Different Neuro-Fuzzy Classification Systems for the Detection of Prostate Cancer in Ultrasonic Images. Proc. IEEE Ultrasonics Symposium 2007. 1201-1204.
  • Medicine Net (2010). Prostate Cancer. Medical Editors:William C. Shiel Jr., MD, FACP, FACR and Dennis Lee, MD, http://www.medicinenet.com/prostate_cancer/.
  • Metlin C., Lee F., Drago J et all (1991). The American cancer society national prostate cancer detection, project: Findings on the detection of early prostate cancer in 2425 men. Cancer. 67: 2949-2958.
  • Nguyen H.P., Krenovich V (2001). Fuzzy logic and its applications in medicine. International Journal of Medical Informatics, 62: 165–173.
  • Ronco A.L., Fernandez R (1999). Improving ultrasonographic diagnosis of prostate cancer with neural networks. Ultrasound in Med. & Biol.. 25(5): pp. 729–733.
  • Saritas I., Allahverdi N., Sert I.U (2003). A fuzzy expert system design for diagnosis of prostate cancer, International Conference On Computer Systems And Technologies - CompSysTech'03. Sofia-Bulgaria. 345 – 351.
  • Seker H., Odeyato M., Petrovic D., Naguib R.N.G (2003). A fuzzy logic based method for prognostic decision making in breast and prostate cancers. IEEE Trans. on Information Technology in Biomedicine. 7(2) : 114-120.

Year 2013, Volume: 1 Issue: 1, 1 - 7, 28.02.2013

İsmail Saritas Novruz Allahverdi İbrahim Sert

Abstract

References

  • Abbod MF, von Keyserlingk DG, Linkens DA (2001). Mahfouf M. Survey of utilization of fuzzy technology in medicine and healthcare. Fuzzy Sets and Systems. 120:331–349.
  • Allahverdi N (2001). Uzman Sistemler Bir Yapay Zeka Uygulaması. Nobel Yayıncılık. Ankara. 1-248.
  • Allahverdi N, Yaldız S (1998). Expert System Applications in Medicine and Example of Design of a Pre-Diagnosis Expert System. Proc. Second Turkish-German Joint Computer Application Days. 175-192.
  • Allahverdi N, Torun S, Saritas I (2007). Design of a fuzzy expert system for determination of coronary heart disease risk. International Conference on Computer Systems and Technologies-CompSysTech’07, June 2007, Rousse, Bulgaria. II.A: 14.1-14.8.
  • Boegla K, Adlassniga KP, Hayashic Y, Rothenfluhd TE, Leiticha H (2002). Knowledge Acquisition in the Fuzzy Knowledge Representation Framework of a Medical Consultation System. Artificial Intelligence in Medicine. Vol. 676 : 1–26.
  • Brawer MK, Kirby R (1999). Prostate Specific Antigen. In: Brawer MK, Kirby R, eds. Prostate Spesific Antigen. 2nd ed. Health Press. 1-96.
  • Cancer Risk Calculator (2012). Forecasting the risk of disease, http://www.compass. fhcrc.org/edrnnci/bin/calculator/.
  • Kaiser Permanente (2006). Healty manager, http://www.kaiserpermanente.org /medicine/.
  • Lorenz A, Blum M, Ermert H, Senge T (2007). Comparison of Different Neuro-Fuzzy Classification Systems for the Detection of Prostate Cancer in Ultrasonic Images. Proc. IEEE Ultrasonics Symposium 2007. 1201-1204.
  • Medicine Net (2010). Prostate Cancer. Medical Editors:William C. Shiel Jr., MD, FACP, FACR and Dennis Lee, MD, http://www.medicinenet.com/prostate_cancer/.
  • Metlin C., Lee F., Drago J et all (1991). The American cancer society national prostate cancer detection, project: Findings on the detection of early prostate cancer in 2425 men. Cancer. 67: 2949-2958.
  • Nguyen H.P., Krenovich V (2001). Fuzzy logic and its applications in medicine. International Journal of Medical Informatics, 62: 165–173.
  • Ronco A.L., Fernandez R (1999). Improving ultrasonographic diagnosis of prostate cancer with neural networks. Ultrasound in Med. & Biol.. 25(5): pp. 729–733.
  • Saritas I., Allahverdi N., Sert I.U (2003). A fuzzy expert system design for diagnosis of prostate cancer, International Conference On Computer Systems And Technologies - CompSysTech'03. Sofia-Bulgaria. 345 – 351.
  • Seker H., Odeyato M., Petrovic D., Naguib R.N.G (2003). A fuzzy logic based method for prognostic decision making in breast and prostate cancers. IEEE Trans. on Information Technology in Biomedicine. 7(2) : 114-120.
There are 15 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

İsmail Saritas

Novruz Allahverdi

İbrahim Sert

Publication Date February 28, 2013
Published in Issue Year 2013 Volume: 1 Issue: 1

Cite

APA Saritas, İ., Allahverdi, N., & Sert, İ. (2013). A fuzzy approach for determination of prostate cancer. International Journal of Intelligent Systems and Applications in Engineering, 1(1), 1-7.
AMA Saritas İ, Allahverdi N, Sert İ. A fuzzy approach for determination of prostate cancer. International Journal of Intelligent Systems and Applications in Engineering. February 2013;1(1):1-7.
Chicago Saritas, İsmail, Novruz Allahverdi, and İbrahim Sert. “A Fuzzy Approach for Determination of Prostate Cancer”. International Journal of Intelligent Systems and Applications in Engineering 1, no. 1 (February 2013): 1-7.
EndNote Saritas İ, Allahverdi N, Sert İ (February 1, 2013) A fuzzy approach for determination of prostate cancer. International Journal of Intelligent Systems and Applications in Engineering 1 1 1–7.
IEEE İ. Saritas, N. Allahverdi, and İ. Sert, “A fuzzy approach for determination of prostate cancer”, International Journal of Intelligent Systems and Applications in Engineering, vol. 1, no. 1, pp. 1–7, 2013.
ISNAD Saritas, İsmail et al. “A Fuzzy Approach for Determination of Prostate Cancer”. International Journal of Intelligent Systems and Applications in Engineering 1/1 (February 2013), 1-7.
JAMA Saritas İ, Allahverdi N, Sert İ. A fuzzy approach for determination of prostate cancer. International Journal of Intelligent Systems and Applications in Engineering. 2013;1:1–7.
MLA Saritas, İsmail et al. “A Fuzzy Approach for Determination of Prostate Cancer”. International Journal of Intelligent Systems and Applications in Engineering, vol. 1, no. 1, 2013, pp. 1-7.
Vancouver Saritas İ, Allahverdi N, Sert İ. A fuzzy approach for determination of prostate cancer. International Journal of Intelligent Systems and Applications in Engineering. 2013;1(1):1-7.
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