Case-Based Reasoning for Stroke Disease Diagnosis

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 si...

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Main Authors: Rumui, Nelson (Author), Harjoko, Agus (Author), Musdholifah, Aina (Author)
Format: EJournal Article
Published: IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia., 2018-01-31.
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LEADER 02642 am a22003133u 4500
001 IJCSS_26331
042 |a dc 
100 1 0 |a Rumui, Nelson  |e author 
100 1 0 |e contributor 
700 1 0 |a Harjoko, Agus  |e author 
700 1 0 |a Musdholifah, Aina  |e author 
245 0 0 |a Case-Based Reasoning for Stroke Disease Diagnosis 
260 |b IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.,   |c 2018-01-31. 
500 |a https://jurnal.ugm.ac.id/ijccs/article/view/26331 
520 |a 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%). 
540 |a Copyright (c) 2018 IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 
540 |a http://creativecommons.org/licenses/by-sa/4.0 
546 |a eng 
690 |a Computer Science 
690 |a case-based reasoning; jaccard coefficient; siriraj; stroke; dense index 
655 7 |a info:eu-repo/semantics/article  |2 local 
655 7 |a info:eu-repo/semantics/publishedVersion  |2 local 
655 7 |2 local 
786 0 |n IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 12, No 1 (2018): January; 33-42 
786 0 |n 2460-7258 
786 0 |n 1978-1520 
787 0 |n https://jurnal.ugm.ac.id/ijccs/article/view/26331/19913 
856 4 1 |u https://jurnal.ugm.ac.id/ijccs/article/view/26331  |z Get Fulltext 
856 4 1 |u https://jurnal.ugm.ac.id/ijccs/article/view/26331/19913  |z Get Fulltext