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008 200707s2018 th uu m rtt 0| a1eng d
035 _a.b12346111
099 9 _aAIT RSPR no.IM-18-01
100 1 _aAgha, Hazrat Ali
245 1 0 _aDevelopment of expert system for diabetes diagnosis
260 _aPathum Thani, Thailand :
_bAsian Institute of Technology,
_c2018
300 _a63 leaves :
_bill.
490 1 _aResearch studies project report ;
_vno. IM-18-01
500 _aA research submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Information Management, School of Engineering and Technology
502 _aResearch studies project report (M. Eng.) - Asian Institute of Technology, 2018
520 _aIn the recent era, expert systems have been developed in large scale which have affected all sectors of human life especially in medicine. The purpose of this study is to analyze risk of diabetes in patients and predict its seriousness by using the classification techniques depending on attained medical datasets. Basically, diabetes is a chronic disease which severely affects the body's ability to use blood sugar properly. Moreover, its common symptoms may include increased thirst and urination, blurred vision, and fatigue. The scary facts about diabetes is its rapid prevalence worldwide as well as its unawareness among the people. Hence, medical practitioners suggest if diabetes could be diagnosed early, it may save lots of lives across the world. For this reason, an expert system is developed that can diagnose diabetes by considering the dataset{u2019}s basic attributes such as age, plasma glucose concentration, triceps skin fold thickness, 2-hour serum insulin, body mass index, and diastolic blood pressure. Notably, this system can predict risk of diabetes by applying decision tree and rule induction data mining techniques to achieve results. Comparatively, decision tree algorithm proved to be better in performance and accuracy than rule induction algorithm. PHP, HTML, phpMyAdmin, Tomcat, Atom IDE were used for the development and implementational purposes. Lastly, system was evaluated with both testing dataset{u2019}s instances and users.
650 0 _aDiabetes
_xDiagnosis
_xProgrammed instruction
650 0 _aData mining
_xProgramming
700 0 _aVatcharaporn Esichaikul,
_eChairperson
700 1 _aSumanta, Guha,
_eExamination Committee
700 1 _aPhan, Minh Dung,
_eExamination Committee
710 2 _aMinistry of Higher Education (MoHE), Afghanistan,
_eScholarship donor
710 2 _aAIT Fellowship ,
_eScholarship donor
810 2 _aAsian Institute of Technology.
_tResearch studies project report ;
_vno. IM-18-01
856 _3Full-Text
_uhttp://203.159.5.9/ait-thesis/detail.php?q=B06932
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