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A Medical Expert System for Prostate Diseases

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A Medical Expert System for Prostate Diseases
HIROFILOS: A Medical Expert System for Prostate Diseases
CONSTANTINOS KOUTSOJANNIS 1, MARIA TSIMARA2, EMAN NABIL1 1 Medical Physics Lab, Department of Physiotherapy TEI of Patras Psaron 6, Aigion 2 Department of Medicine University of Patras Rion, Patras GREECE ckoutsog@teipat.gr, http://aigio.teipat.gr
Abstract: - Prostate gland diseases, including cancer are estimated to be one of the leading cause of male death worldwide and its management is based on guidelines regarding diagnosis, evaluation, treatment and continuing care. In this study a fuzzy expert system for diagnosing, and learning purpose of the prostate diseases is described. HIROFILOS is a fuzzy expert system for diagnosis and treatment of prostate diseases according to symptoms that are realized in one patient and usually recorded through his clinical examination as well as specific test results. The user-friendly proposed intelligent system is accommodated on a hospital web page for use as a decision support system for resident doctors, as an educational tool for medical students, as well as, an introductory advisory tool for interested patients. It is based on knowledge representation provided from urology experts in combination with rich bibliographic search and study ratified with statistical results from clinical practice. Preliminary experimental results on a real patient hospital database provide an acceptable performance that can be improved using more than one computational intelligence approaches in the future. Key-Words: - Prostate disease, , urology, medical expert system, fuzzy logic.

1 Introduction
Prostate gland diseases, including cancer are estimated to be one of the leading cause of male death worldwide and its management is based on guidelines regarding diagnosis, evaluation, treatment and continuing care. Prostate cancer is the most common noncutaneous cancer among males [1]. The diagnosis and treatment of prostate cancer continue to evolve. With the development of



References: [1] European Association of Urology, Guidelines 2007, http://www.uroweb.org/professionalresources/guidelines/. [2] Pereira M, Schaefer M, B Marques J. Remote expert system of support the prostate cancer diagnosis. Conf Proc IEEE Eng Med Biol Soc. 2004;5:3412-5. Llobet R, Pérez-Cortés [3] C, Toselli AH, Juan A. Computer-aided detection of prostate cancer. Int J Med Inform. 2007 Jul;76(7):547-56. Epub 2006 Apr 18. [4] Chang PL, Wang TM, Huang ST, Hsieh ML, Tsui KH, Lai RH. Use of a medical decision support system to improve the preoperative diagnosis of prostate cancer with pelvic lymph node metastases. Changgeng Yi Xue Za Zhi. 1999 Dec;22(4):556-64. [5] Chang PL, Li YC, Wang TM, Huang ST, Hsieh ML, Tsui KH. Evaluation of a decision-support system for preoperative staging of prostate cancer. Med Decis Making. 1999 OctDec;19(4):419-27. [6] Anagnostou T, Remzi M, Lykourinas M, Djavan B. Artificial neural networks for decision-making in urologic oncology. Eur Urol. 2003 Jun;43(6):596-603. [7] Bagli DJ, Agarwal SK, Venkateswaran S, Shuckett B, Khoury AE, Merguerian PA, McLorie GA, Liu K, Niederberger CS. Artificial 6

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