Case-Based Reasoning for the Diagnosis of Acute Respiratory Infections Using Minkowski Distance

Abstract. Hypertension is one of the health problems priority in the world because of the increasing of life expectancy and an unhealthy lifestyle. Many people with hypertension are unreachable and undiagnosed by a health worker and they do not do treatment according to the health recommendation. The Case-Based Reasoning (CBR) Method can be applied to solve the new cases in diagnosed hypertension using the answer or experience from the old case by comparing the new case and the old case. In order to do not use all the basic case data for finding a similar case, it makes an indexing process is needed. The DBSCAN algorithm implementation as indexing method is expected to improve the time and memory efficiency in CBR, especially during the retrieval process. The result of the CBR test with the cluster-indexing has a better accuracy and time process than the non-indexing CBR. The minimum parameter points and epsilon that has been chosen for clustering on hypertension data case is the combination of epsilon score 9 and minimum points score 3 with the silhoutte coefficient score 0.240 and average cluster time 0.541 seconds. The Minkowski Distance method has better accuracy than the Euclidean Distance method because by the threshold score ≥ 0.9 the CBR system with the Minkowski distance method is able to diagnose the disease with 100 % accuracy and the average best retrieval time, it is 0.0586 second Abstrak. Hipertensi menjadi salah satu prioritas masalah kesehatan di dunia karena peningkatan angka harapan hidup dan gaya hidup yang tidak sehat. Banyak penderita hipertensi yang tidak terjangkau dan terdiagnosis oleh tenaga kesehatan serta tidak menjalani pengobatan sesuai anjuran kesehatan. Metode Case-Based Reasoning (CBR) dapat diaplikasikan untuk menyelesaikan masalah baru dalam diagnosis penyakit hipertensi menggunakan jawaban atau pengalaman dari masalah lama dengan membandingkan kasus baru dengan kasus lama. Supaya proses pencarian kasus yang mirip tidak perlu melibatkan seluruh data pada basis kasus,maka diperlukan proses indexing. Implementasi algoritme DBSCAN sebagai metode indexing diharapkan dapat meningkatkan efisiensi waktu dan memori pada CBR khususnya ketika proses retrival. Hasil pengujian CBR dengan cluster-indexing memiliki akurasi dan waktu proses yang lebih baik dari pada CBR non-indexing. Parameter minimum points dan epsilon yang dipilih untuk melakukan clustering pada data kasus penyakit hipertensi adalah kombinasi epsilon 9 dan minimum points 3 dengan nilai silhoutte coeffisien 0.240 dan waktu klaster rata-rata 0.541 detik. Metode minkowski distance memiliki akurasi yang lebih baik dari pada metode euclidean distance, karena dengan threshold ≥ 0.9 sistem CBR dengan metode minkowski distance mampu mendignosis penyakit dengan akurasi 100% dan waktu retrieve rata-rata terbaik yaitu 0.0586 detik.

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Sistem Pakar Menggunakan Metode Case Based Reasoning dalam Akurasi Penyakit Disebabkan oleh Bakteri Staphylococcus Aureus

Jurnal Sistim Informasi dan Teknologi ◽

10.37034/jsisfotek.v3i1.94 ◽

2020 ◽

Author(s):

Surya Aulia Rahman ◽

S Sumijan

Keyword(s):

Staphylococcus Aureus ◽

Respiratory Infections ◽

Bacterial Disease ◽

Case Based Reasoning ◽

Skin Infections ◽

Highly Pathogenic ◽

Eye Infections ◽

Serious Infections ◽

Tract Infections ◽

Case Based

Staphylococcus aureus is the most worrisome bacteria in the world of health because it is highly pathogenic and can cause serious infections in previously healthy individuals. Staphylococcus aureus has gram-positive cells, round (cocci) 0.7-0.9 µm in diameter, non-spore-forming, non-motile, facultative anoerobes, in colony shaped like a grape string. This bacterial infection in humans varies in severity, from minor skin infections (furunculosis and impertigo), urinary tract infections, respiratory infections, to eye infections. This causes many patients to need an expert (doctor) to consult about the symptoms that a patient appears or experiences and the risk factors felt by the patient. So they conducted this research using the Case Based Reasoning (CBR) method which consists of 4 steps, namely retrieve, reuse, retain and revise. By using the case-based reasoning method for a problem with the staphylococcus aureus bacterial disease, it is easier for a patient to find treatment and a solution. With an expert system using this method (case based reasoning), experts (doctors) can easily find out what diseases are suffered by staphylococcus. That way, patients with staphylococcus disease are prepared to deal with the disease they are suffering from.

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Case Based Reasoning untuk Diagnosis Penyakit Jantung Menggunakan Metode Minkowski Distance

INTECOMS Journal of Information Technology and Computer Science ◽

10.31539/intecoms.v1i1.170 ◽

2018 ◽

Vol 1 (1) ◽

pp. 119-123

Author(s):

Eka Wahyudi ◽

Novi Indah Pradasari

Keyword(s):

Heart Disease ◽

Computer System ◽

Medical Records ◽

Disease Diagnosis ◽

Case Based Reasoning ◽

Test Results ◽

Minkowski Distance ◽

Heart Disease Diagnosis ◽

System Knowledge ◽

Case Based

Case Based Reasoning is a computer system that used for reasoning old knowledge to solve new problems. It works by looking at the closest old case to the new case. This research attempts to establish a system of CBR for diagnosing heart disease. The diagnosis process is done by inserting new cases containing symptoms into the system, then the similarity value calculation between cases uses the minkowski distance similarity. Case taken is the case with the highest similarity value. If a case does not succeed in the diagnosis or threshold less than 0.80, the case will be revised by experts. Revised successful cases are stored to add the system knowledge. Method with the best diagnostic result accuracy will be used in building the CBR system for heart disease diagnosis. The test results using medical records data validated by expert indicate that the system is able to recognize diseases heart using minskowski distance similarity correctly of 100 percent. Using minkowski get accuracy of 100 percent. Keywords : Case Based Reasoning, Minkowski Distance Similarity.

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DIAGNOSIS PENYAKIT HIPERTENSI MENGGUNAKAN METODE CASE-BASED REASONING

IJIS - Indonesian Journal On Information System ◽

10.36549/ijis.v5i1.87 ◽

2020 ◽

Vol 5 (1) ◽

Author(s):

Amalia Beladinna Arifa ◽

Gita Fadila Fitriana

Keyword(s):

Cross Validation ◽

Case Based Reasoning ◽

Minkowski Distance ◽

Fold Cross Validation ◽

Case Based

Hipertensi adalah kondisi ketika tekanan darah pada pembuluh darah bersih meningkat secara kronik. Jika tidak segera ditangani dapat menyebabkan peningkatan resiko kejadian penyakit lainnya, misalnya kardiovaskuler, serebrovaskuler dan renovaskuler. Diagnosis penyakit hipertensi perlu ditegakkan sedini mungkin guna menurunkan peningkatan resiko kejadian penyakit lainnya. Penelitian ini bertujuan menghasilkan sistem yang mengimplementasikan metode Case-Based Reasoning yang dapat membantu paramedis untuk mendiagnosis penyakit hipertensi. Implementasi sistem dirancang menggunakan bahasa pemrograman PHP serta penyimpanan data kasus menggunakan MySQL. Kasus-kasus penyakit hipertensi yang sudah berhasil ditangani oleh dokter dijadikan sebagai data acuan untuk mendiagnosis kasus hipertensi yang baru. Kasus baru yang berisi faktor resiko, gejala dan riwayat penyakit selanjutnya dicari kemiripannya dengan kasus-kasus lama dengan cara menghitung nilai similaritas menggunakan Minkowski Distance. Pengujian dilakukan pada 172 data menggunakan 10-fold Cross-Validation. Hasil perhitungan dengan menetapkan threshold sebesar 0,90 didapatkan tingkat akurasi sebesar 94,71%. Hasil penelitian menunjukkan implementasi Case-Based Reasoning dapat digunakan untuk melakukan diagnosis penyakit hipertensi

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Local Triangular Kernel-Based Clustering (LTKC) for Case Indexing on Case-Based Reasoning

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ◽

10.22146/ijccs.30423 ◽

2018 ◽

Vol 12 (2) ◽

pp. 139

Author(s):

Damar Riyadi ◽

Aina Musdholifah

Keyword(s):

Heart Disease ◽

Thyroid Disease ◽

Euclidean Distance ◽

Manhattan Distance ◽

Case Based Reasoning ◽

Minkowski Distance ◽

Retrieval Time ◽

Accuracy Comparison ◽

Speed Up ◽

Case Based

This study aims to improve the performance of Case-Based Reasoning by utilizing cluster analysis which is used as an indexing method to speed up case retrieval in CBR. The clustering method uses Local Triangular Kernel-based Clustering (LTKC). The cosine coefficient method is used for finding the relevant cluster while similarity value is calculated using Manhattan distance, Euclidean distance, and Minkowski distance. Results of those methods will be compared to find which method gives the best result. This study uses three test data: malnutrition disease, heart disease, and thyroid disease. Test results showed that CBR with LTKC-indexing has better accuracy and processing time than CBR without indexing. The best accuracy on threshold 0.9 of malnutrition disease, obtained using the Euclidean distance which produces 100% accuracy and 0.0722 seconds average retrieval time. The best accuracy on threshold 0.9 of heart disease, obtained using the Minkowski distance which produces 95% accuracy and 0.1785 seconds average retrieval time. The best accuracy on threshold 0.9 of thyroid disease, obtained using the Minkowski distance which produces 92.52% accuracy and 0.3045 average retrieval time. The accuracy comparison of CBR with SOM-indexing, DBSCAN-indexing, and LTKC-indexing for malnutrition diseases and heart disease resulted that they have almost equal accuracy.

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Sistem Pakar Menggunakan Metode Case Based Reasoning dalam Akurasi Penyakit Disebabkan oleh Bakteri Staphylococcus Aureus

Jurnal Sistim Informasi dan Teknologi ◽

10.37034/jsisfotek.v3i1.38 ◽

2021 ◽

pp. 13-19

Author(s):

Surya Aulia Rahman ◽

S Sumijan

Keyword(s):

Staphylococcus Aureus ◽

Respiratory Infections ◽

Bacterial Disease ◽

Case Based Reasoning ◽

Skin Infections ◽

Highly Pathogenic ◽

Eye Infections ◽

Serious Infections ◽

Tract Infections ◽

Case Based

Staphylococcus aureus is the most worrisome bacteria in the world of health because it is highly pathogenic and can cause serious infections in previously healthy individuals. Staphylococcus aureus has gram-positive cells, round (cocci) 0.7-0.9 µm in diameter, non-spore-forming, non-motile, facultative anoerobes, in colony shaped like a grape string. This bacterial infection in humans varies in severity, from minor skin infections (furunculosis and impertigo), urinary tract infections, respiratory infections, to eye infections. This causes many patients to need an expert (doctor) to consult about the symptoms that a patient appears or experiences and the risk factors felt by the patient. So they conducted this research using the Case Based Reasoning (CBR) method which consists of 4 steps, namely retrieve, reuse, retain and revise. By using the case-based reasoning method for a problem with the staphylococcus aureus bacterial disease, it is easier for a patient to find treatment and a solution. With an expert system using this method (case based reasoning), experts (doctors) can easily find out what diseases are suffered by staphylococcus. That way, patients with staphylococcus disease are prepared to deal with the disease they are suffering from.

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Case-Based Reasoning untuk Diagnosis Penyakit Jantung

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) ◽

10.22146/ijccs.15523 ◽

2017 ◽

Vol 11 (1) ◽

pp. 1 ◽

Cited By ~ 4

Author(s):

Eka Wahyudi ◽

Sri Hartati

Keyword(s):

Heart Disease ◽

Euclidean Distance ◽

Nearest Neighbor ◽

Disease Diagnosis ◽

Case Based Reasoning ◽

Test Results ◽

Minkowski Distance ◽

Heart Disease Diagnosis ◽

Similarity Method ◽

Case Based

Case Based Reasoning (CBR) is a computer system that used for reasoning old knowledge to solve new problems. It works by looking at the closest old case to the new case. This research attempts to establish a system of CBR for diagnosing heart disease. The diagnosis process is done by inserting new cases containing symptoms into the system, then the similarity value calculation between cases uses the nearest neighbor method similarity, minkowski distance similarity and euclidean distance similarity. Case taken is the case with the highest similarity value. If a case does not succeed in the diagnosis or threshold <0.80, the case will be revised by experts. Revised successful cases are stored to add the systemknowledge. Method with the best diagnostic result accuracy will be used in building the CBR system for heart disease diagnosis. The test results using medical records data validated by expert indicate that the system is able to recognize diseases heart using nearest neighbor similarity method, minskowski distance similarity and euclidean distance similarity correctly respectively of 100%. Using nearest neighbor get accuracy of 86.21%, minkowski 100%, and euclidean 94.83%

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Case-Based Reasoning (CBR): Final Report

PsycEXTRA Dataset ◽

10.1037/e508702010-001 ◽

2006 ◽

Keyword(s):

Final Report ◽

Case Based Reasoning ◽

Case Based

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PERAN IBU DALAM PENINGKATAN SISTEM IMUN ANAK DENGAN INFEKSI SALURAN PERNAFASAN AKUT

Jurnal Keperawatan ◽

10.32583/keperawatan.v11i2.422 ◽

2019 ◽

Vol 11 (2) ◽

pp. 79-86

Author(s):

Cindy Ayustin Noya ◽

Angkit Kinasih ◽

Venti Agustina ◽

R.Rr Maria Dyah Kurniasari

Keyword(s):

Immune System ◽

Acute Respiratory Infection ◽

Lower Respiratory Tract ◽

Research Method ◽

Respiratory Infections ◽

Acute Respiratory Infections ◽

Clean Environment ◽

History Of ◽

Qualitative Descriptive

Infeksi saluran pernafasan akut atau yang sering disebut ISPA merupakan infeksi pada saluran pernafasan baik saluran pernafasan atas atau bawah.ISPA juga kebanyakan terjadi pada anak balita karena daya tahan tubuh mereka tidak kuat dalam menghadapi penyakit ISPA. ISPA mengakibatkan kematiansekitar15%-20% per tahun pada usia balita di Negara berkembang. Tujuan penelitian ini adalah untuk mengetahui dan menganalisa peran ibu dalam meningkatkan sistem imun anak dengan ISPA.Metode penelitian yang digunakan dalam penelitian ini adalah kualitatif deskriptif dengan sampel purposive sampling.Populasi dan sampel penelitian ini adalah ibu yang mempunyai anak dengan riwayat dan saat ini menderita penyakit ISPA di Batu Gajah Kota Ambon.Partisipan dalam penelitian ini berjumlah 5 orang. Hasil dari penelitian mendapati 4 kategori yaitu pemberian nutrisi pada anak untuk memenuhi kebutuhan agar sistem imunnya terjaga, kebersihan lingkungan, peran ibu dalam melakukan pencegahan pada anaknya yang mengalami ISPA, dan peran ibu dalam menjaga dan mempertahankan kesehatan anaknya. Kata kunci: peran ibu, sistem imun, ispa THE ROLE OF MOTHERS IN INCREASING IMMUNE SYSTEM OF CHILDREN WITH ACUTE RESPIRATORY INFECTION ABSTRACT Acute respiratory infections or often called ARI is an infection of the upper or lower respiratory tract. ARI occurs mostly in children under the age of five because their endurance is not strong in dealing with ARI. ARI results in deaths of around 15%-20% per year at the age of under-five in developing countries. The purpose of this study was to determine and analyze the role of mothers in improving the immune system of children against ARI. The research method used in this study was qualitative descriptive with a purposive sampling sample. Respondents and samples of this study were five mothers who had children with a history of ARI and currently suffering from the disease in Batu Gajah, Ambon City. The results of the study found 4 categories, namely providing nutrition to children to meet their needs so that their immune systems are maintained, clean environment, mother's role in preventing children with ARI, and mother's role to preserve and maintain the health of their children. The findings indicated that in terms of coping or improving the immune system of a child to avoid ARI, it is necessary to have role the of mothers in providing nutrition so that the immune system is boosted, besides that the mother can prevent and protect her child from various diseases, especially ARI. Keywords: role of mothers, immune system, acute respiratory infections

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