Title :
Fuzzy logic application in gynecology: A case study
Author :
Sardesai, Anjali ; Sambarey, Pradip ; Kharat, Vilas ; Deshpande, A.
Author_Institution :
Dept. of Comput. Sci., Univ. of Pune, Pune, India
Abstract :
In medical diagnosis, the descriptions of disease entities use linguistic expressions that are inherently imprecise/vague/ fuzzy/ambiguous which form the scaffold of the medical knowledge of a physician. In our view, overall approach in gynecological disease diagnosis could be divided in three distinct stages. Stage 1 refers to initial screening process in order to arrive at a single disease diagnosis for the patients, and based only on the subjective information provided by patients to the physician. In stage 2, the patient who has not received a single diagnostic label in stage 1, is further investigated for single disease diagnosis using the parameter past history. If stage 2 fails to arrive at a single disease diagnosis for a patient then physical examination and various tests like imaging tests, blood tests, etc. are conducted and the test results are processed in stage 3. The paper presents the research findings with a case study focused only on stage 2 using type 1 fuzzy inference system. We have identified 29 out of 226 patients satisfying past history criteria to achieve single disease diagnosis wherein in stage 1, 50 patients were correctly diagnosed.
Keywords :
decision support systems; diseases; fuzzy logic; fuzzy reasoning; gynaecology; medical administrative data processing; medical diagnostic computing; patient diagnosis; MDDS; blood tests; disease descriptions; fuzzy logic application; gynecological disease diagnosis; gynecology; imaging tests; initial screening process; linguistic expressions; medical decision support systems; medical diagnosis; medical knowledge; parameter past history; single diagnostic label; single disease diagnosis; type 1 fuzzy inference system; Diseases; Fuzzy logic; Fuzzy sets; History; Medical diagnostic imaging; expert knowledgebase; gynecology disease diagnosis; medical decision system; type 1 fuzzy inference system;
Conference_Titel :
Informatics, Electronics & Vision (ICIEV), 2014 International Conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4799-5179-6
DOI :
10.1109/ICIEV.2014.6850715