کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
385740 660872 2011 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Clinical decision support system (DSS) in the diagnosis of malaria: A case comparison of two soft computing methodologies
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Clinical decision support system (DSS) in the diagnosis of malaria: A case comparison of two soft computing methodologies
چکیده انگلیسی

The purpose of this study is to make the case for the utility of decision support systems (DSS) in the diagnosis of malaria and to conduct a case comparison of the effectiveness of the fuzzy and the AHP methodologies in the medical diagnosis of malaria, in order to provide a framework for determining the appropriate kernel in a fuzzy–AHP hybrid system. The combination of inadequate expertise and sometimes the vague symptomatology that characterizes malaria, exponentially increase the morbidity and mortality rates of malaria. The task of arriving at an accurate medical diagnosis may sometimes become very complex and unwieldy. The challenge therefore for physicians who have limited experience investigating, diagnosing, and managing such conditions is how to make sense of these confusing symptoms in order to facilitate accurate diagnosis in a timely manner.The study was designed on a working hypothesis that assumed a significant difference between these two systems in terms of effectiveness and accuracy in diagnosing malaria. Diagnostic data from 30 patients with confirmed diagnosis of malaria were evaluated independently using the AHP and the fuzzy methodologies. Results were later compared with the diagnostic conclusions of medical experts. The results of the study show that the fuzzy logic and the AHP system can successfully be employed in designing expert computer based diagnostic system to be used to assist non-expert physicians in the diagnosis of malaria. However, fuzzy logic proved to be slightly better than the AHP, but with non-significant statistical difference in performance.

Research highlights
► Decision support systems (DSS) are effective as diagnosis aids to medical doctors.
► Fuzzy logic and AHP were compared as tools for building clinical diagnosis systems with malaria as case study.
► Fuzzy logic is slightly better than AHP in obtaining matching diagnosis of malaria, when compared with diagnosis made by medical experts.
► The difference between these two systems is nevertheless not statistically significant.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 38, Issue 3, March 2011, Pages 1537–1553
نویسندگان
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