IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Vol 12, No 1 (2018): January

Case-Based Reasoning for Stroke Disease Diagnosis

Nelson Rumui (Master Program of Computer Science
FMIPA UGM, Yogyakarta)

Agus Harjoko (Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta)
Aina Musdholifah (Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta)



Article Info

Publish Date
31 Jan 2018

Abstract

Stroke is a type of cerebrovascular disease that occurs because blood flow to the brain is disrupted. Examination of stroke accurately using CT scan, but the tool is not always available, so it can be done by the Siriraj Score. Each type of stroke has similar symptoms so doctors should re-examine similar cases prior to diagnosis. The hypothesis of the Case-based reasoning (CBR) method is a similar problems having similar solution.This research implements CBR concept using Siriraj score, dense index and Jaccard Coeficient method to perform similarity calculation between cases.The test is using k-fold cross validation with 4 fold and set values of threshold (0.65), (0.7), (0.75), (0.8), (0.85), (0.9), and (0.95). Using 45 cases of data test  and 135 cases of case base. The test showed that threshold of 0.7 is suitable to be applied in sensitivity (89.88%) and accuracy (84.44% for CBR using indexing and 87.78% for CBR without indexing). Threshold of 0.65 resulted high sensitivity  and accuracy but showed many cases of irrelevant retrieval results. Threshold (0.75), (0.8), (0.85), (0.9) and (0.95) resulted in sensitivity (65.48%, 59.52%, 5.95%, 3,57% and 0%) and accuracy of CBR using indexing (61.67%, 55.56%, 5.56%, 3.33%, and 0%) and accuracy of CBR without indexing (62.78% 56.67%, 55.56%, 5.56%, 3.33%, and 0%).

Copyrights © 2018






Journal Info

Abbrev

ijccs

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so ...