A Proposed Fuzzy Model for Diseases Diagnosis
Eman Nabil Alkholy1, Amal Elsayed Aboutabl2, Mohamed Hassan Haggag3
1Eman Nabil Alkholy*, Department of Computer Science and Engineering, Helwan University, Egypt.
2prof. Amal Elsayed Aboutabl, Department of Computer Science and Engineering, Helwan University, Egypt.
3Prof. Mohamed Hassan Haggag, Department of Computer Science and Engineering, Helwan University, Egypt.
Manuscript received on January 22, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 4300-4304 | Volume-9 Issue-3, February 2020. | Retrieval Number: C6419029320/2020©BEIESP | DOI: 10.35940/ijeat.C6419.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Decision making has become a problem in environments full of uncertain, vague and imprecise information. They face many problems to train computer systems to simulate human thinking to make the right decision. Different methodologies and approaches have been used to train computers to understand and mimic human thinking. This paper proposes a fuzzy model for a bone disease to have the right diagnosis answer, as a human expertise doctor. and to prove that using fuzzy logic has a significant ability to mimic human thinking. The model accepts inputs in the different forms as physiological and clinical parameters and all data based on medical expertise, using a rule-based fuzzy system approach applied with fourteen rules to have final accurate output decisions. it has been tested in the orthopedic unit against the real existing diagnosis answer from expertise doctor and found that is capable of assisting medical experts in diagnosing diseases and provide good health services to their patients.
Keywords: Fuzzy logic, medical Diagnosis, Artificial Intelligence.