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    Design of Web-Based Fuzzy Input Expert System for the Analysis of Serology Laboratory Tests
    (SPRINGER, 2012) Basciftci, Fatih; Incekara, Hayri
    In this study, it is aimed, using the Web-based Expert System with Fuzzy Input (WESFI), to convert the patients' (users') Serology Laboratory Tests (SLT) results to linguistic statements (low, normal, high) and analyzing those, give a feedback to the user (patient) of the potential signs of disease. The feedbacks given to the patients are the existing interpretations in the database, which were prepared by doctors before. Furthermore, the SLT terms (Brucella Coombs, Ama, P-Protein etc.) are explained in a way that the user can understand. The WESFI is published with an interface on the web environment. In order to determine the rate of the success of the WESFI, users evaluated the system answering the "How do you find the evaluation?" question. The question has been answered by 461 users. As a result it is observed that 90% of female users, 92% of male users and 91% of all users found the system useful.
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    Web based medical decision support system application of Coronary Heart Disease diagnosis with Boolean functions minimization method
    (PERGAMON-ELSEVIER SCIENCE LTD, 2011) Basciftci, Fatih; Incekara, Hayri
    Heart and vein diseases are one of the most important health problems. The number of the people who died of heart and vein diseases is more than the number of the people who died of all other health problems and natural disasters. In order to decrease this number, the intervention must be started very earlier and people must be informed about this subject. In this study, Medical Expert System has been used all the probabilities of CHD has been determined (9 symptoms, 2(9) = 512 different occasions) and from these probabilities, an accuracy table has been formed. This accuracy table has been simplified with the Boolean functions simplifying methods. 94 rules have been achieved by the Boolean functions minimization method. The rules achieved have formed the Expert System's rule base. 303 patients' values have been compared with the realized Expert System. The Medical Expert System which was formed as a result of the evaluation has evaluated men with 86.5%, women with 84.5% and in general with 86.1% accuracy rate. (C) 2011 Elsevier Ltd. All rights reserved.