Designing and Implementation of Fuzzy Case-based Reasoning System on Android Platform Using Electronic Discharge Summary of Patients with Chronic Kidney Diseases

摘要

Introduction: Case-based reasoning (CBR) systems are one of the effective methods to find the nearestudsolution to the current problems. These systems are used in various spheres as well as industry, business,udand economy. The medical field is not an exception in this regard, and these systems are nowadays usedudin the various aspects of diagnosis and treatment. Methodology: In this study, the effective parametersudwere first extracted from the structured discharge summary prepared for patients with chronic kidneyuddiseases based on data mining method. Then, through holding a meeting with experts in nephrologyudand using data mining methods, the weights of the parameters were extracted. Finally, fuzzy systemudhas been employed in order to compare the similarities of current case and previous cases, and theudsystem was implemented on the Android platform. Discussion: The data on electronic discharge recordsudof patients with chronic kidney diseases were entered into the system. The measure of similarity wasudassessed using the algorithm provided in the system, and then compared with other known methodsudin CBR systems. Conclusion: Developing Clinical fuzzy CBR system used in Knowledge managementudframework for registering specific therapeutic methods , Knowledge sharing environment for expertsudin a specific domain and Powerful tools at the point of care .