Research Article
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Year 2020, Volume: 5 Issue: 3, 121 - 131, 31.12.2020
https://doi.org/10.30931/jetas.857665

Abstract

References

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  • [18] Wang, F., LI, Y., “An improved Apriori algorithm based on matrix”, 12’th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) 2020. 28-29 Feb. 2020. Phuket, Thailand, (2020) : 488-491.
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  • [20] Karimtabar, N., Shayegan Fard M.J., “An extension of the apriori algorithm for finding frequent items”, 2020 6’th International Conference on Web Research (ICWR) 2020. 22-23 Apr. 2020. Tehran, Iran, (2020) : 330-334.
  • [21] Balaban, M.E., Kartal, E., “Veri madenciliği ve makine öğrenmesi temel algoritmaları ve R Dili ile Uygulamalar”, 2. Basım, İstanbul, Türkiye: Çağlayan Kitap & Yayıncılık&Eğitim, (2018).
  • [22] Dua, D., Graff, C., “UCI machine learning repository”, University of California, School of Information and Computer Science. Irvine, USA, (2019).

Using Apriori Data Mining Method in COVID-19 Diagnosis

Year 2020, Volume: 5 Issue: 3, 121 - 131, 31.12.2020
https://doi.org/10.30931/jetas.857665

Abstract

Corona virus 2019 (COVID-19) disease has spread all over the world and many people have died due to this disease. PCR (Polymerase Chain Reaction) tests are mostly applied to detect people who have this disease. However, in some cases, it is necessary to wait twenty-four hours for the results of this test. In such cases, the treatment and isolation process of the patient may be delayed. Therefore, the rapid commencement of treatment and isolation process by analyzing the symptoms, are of great importance. Using data mining methods can be carried out quickly specify analysis. Association rule algorithms are also among data mining methods. The most common SETM, AIS and Apriori association rule algorithms are encountered. The most widely used is the Apriori association algorithm. Using this algorithm, the frequency and association rates of the data are found in the data set. In this study, it has been shown that association rules calculated by Apriori algorithm can be used in the diagnosis of COVID-19. By using the COVID-19 Survilance data set, the association rates of the disease symptoms specified in the ICD (International Classification of Diseases) International Classification of Diseases codes were determined. According to the results obtained; it has been observed that the patients with these symptoms are 100% definitely infected with COVID-19 disease when the disease symptoms represented by the A01, A02 and A04 disease codes are together.

References

  • [1] Wiguna, W., Riana, D., “Diagnosis of Coronavirus disease 2019(Covid-19) surveillance using C4.5 algorithm”, Journal PILAR Nusa Mandiri, 16 (2020) : 71-80.
  • [2] Jalota, C., Agrawal, R., “Analysis of educational data mining using classification”, 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (Com-IT-Con); 14th -16th Feb 2019; India. (2019) : 243-247.
  • [3] Kumar S., Singh, M., “Big data analytics for healthcare industry: impact, applications and tools”, Big Data Mining and Analytic, 2 (2019) : 48-57.
  • [4] Kotturu, P.K., Kumar, A., “Data mining visualization with the impact of nature inspired algorithms in big data”, Proceedings of the Fourth International Conference on Trends in Electronics and Informatics (ICOEI 2020); 16-18, April 2020. India. Tirunelveli, (2020) : 664-668.
  • [5] Cui X., Yang, S., Wang, D., “An algorithm of apriori based on medical big data and cloud computeing”, 3th Conferance of Computational Interdisciplinary Science; 7-10 November 2016; Campos, Brazil, (2016) : 361-365.
  • [6] Chen, Y.C., Chang, Y.T., Kan, Y.S., Chen, R.S., Wu, S.F., “Using data mining technique to improve billing system performance in semiconductor industry”, International Conference on Information and Computer Technologies; 23-25 March 2018, Dekalb, United States, (2018) : 1-4.
  • [7] Laksito, A.D., Kusrini, K., “Apriori algorithm optimization using temporary table”, International Conference on Information and Communications Technology (ICOIACT); 24-25 July 2019. Yogyakarta, Indonesia, (2019) : 560-565.
  • [8] Yin, Y., Long, L., Deng, X., “Dynamic data mining of sensor data”, IEEE Access, (2020) : 8:41637-61648.
  • [9] Wu, X., Zhu, X., “Mining with noise knowledge: Error-aware data mining”, IEEE Transactions on Systems Man and Cybernetics, 38 (2008) : 917-932.
  • [10] Hirano, S., Tsumoto, S., “Frequent temporal pattern mining for medical data based on ranged Relations”, IEEE International Conference on Data Mining; 18-21 November 2017. New Orleans, United States (2017) : 612-616.
  • [11] Ya, L., Lei, Y., Li, W., “Chun M, Guiming Y. “Application research of apriori algorithm based on matrix multiplication in children’s drug interaction”, 12’th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) 2020; 28-29 Feb. 2020. Phuket Thailand, (2020) : 507-512.
  • [12] Gutub, A., Ahmed, S., "Trialing a smart face-recognition computer system to recognize lost people visiting the two holy mosques", Arab Journal of Forensic Sciences & Forensic Medicine (AJFSFM), 8 (2019) : 1120-1133.
  • [13] Alassaf, N., Gutub, A., "Simulating light-weight-cryptography implementation for IoT healthcare data security applications", International Journal of E-Health and Medical Communications (IJEHMC), 4 (2019) : 1-15.
  • [14] World Health Organization (WHO), “International statistical classification of diseases and related health problems”, 10’th Revision (ICD-10 manual), Centers for Disease Control and Prevention, 1 (2005) : 1-1268.
  • [15] T.C. Sağlık Bakanlığı Halk Sağlığı Genel Müdürlüğü, “COVID-19 (SARS-Cov-2 Enfeksiyonu rehberi) Bilim Kurulu Çalışması”, 12 Nisan 2020, Ankara, (2020) : 1-98.
  • [16] Zerman, M., “Birliktelik kuralı algoritmaları ile büyük veriler üzerinde analitik analizler: havaalanı örneği”. Yüksek Lisans Tezi, Haliç Üniversitesi, İstanbul, Tükiye, (2018).
  • [17] Singh, J., Ram, H., Sodhi, J.S., “Improving efficient apriori algorithm using enhanced transaction reduction”, International Journal of Scientific and Research Publications, 3 (2013) : 1-4.
  • [18] Wang, F., LI, Y., “An improved Apriori algorithm based on matrix”, 12’th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) 2020. 28-29 Feb. 2020. Phuket, Thailand, (2020) : 488-491.
  • [19] Silahtaroğlu, G., “Veri madenciliği (Kavram ve algoritmaları)”, 3. Basım, İstanbul, Türkiye: Papatya Yayıncılık Eğitim, (2016).
  • [20] Karimtabar, N., Shayegan Fard M.J., “An extension of the apriori algorithm for finding frequent items”, 2020 6’th International Conference on Web Research (ICWR) 2020. 22-23 Apr. 2020. Tehran, Iran, (2020) : 330-334.
  • [21] Balaban, M.E., Kartal, E., “Veri madenciliği ve makine öğrenmesi temel algoritmaları ve R Dili ile Uygulamalar”, 2. Basım, İstanbul, Türkiye: Çağlayan Kitap & Yayıncılık&Eğitim, (2018).
  • [22] Dua, D., Graff, C., “UCI machine learning repository”, University of California, School of Information and Computer Science. Irvine, USA, (2019).
There are 22 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Research Article
Authors

Ahmet Çelik 0000-0002-6288-3182

Publication Date December 31, 2020
Published in Issue Year 2020 Volume: 5 Issue: 3

Cite

APA Çelik, A. (2020). Using Apriori Data Mining Method in COVID-19 Diagnosis. Journal of Engineering Technology and Applied Sciences, 5(3), 121-131. https://doi.org/10.30931/jetas.857665
AMA Çelik A. Using Apriori Data Mining Method in COVID-19 Diagnosis. JETAS. December 2020;5(3):121-131. doi:10.30931/jetas.857665
Chicago Çelik, Ahmet. “Using Apriori Data Mining Method in COVID-19 Diagnosis”. Journal of Engineering Technology and Applied Sciences 5, no. 3 (December 2020): 121-31. https://doi.org/10.30931/jetas.857665.
EndNote Çelik A (December 1, 2020) Using Apriori Data Mining Method in COVID-19 Diagnosis. Journal of Engineering Technology and Applied Sciences 5 3 121–131.
IEEE A. Çelik, “Using Apriori Data Mining Method in COVID-19 Diagnosis”, JETAS, vol. 5, no. 3, pp. 121–131, 2020, doi: 10.30931/jetas.857665.
ISNAD Çelik, Ahmet. “Using Apriori Data Mining Method in COVID-19 Diagnosis”. Journal of Engineering Technology and Applied Sciences 5/3 (December 2020), 121-131. https://doi.org/10.30931/jetas.857665.
JAMA Çelik A. Using Apriori Data Mining Method in COVID-19 Diagnosis. JETAS. 2020;5:121–131.
MLA Çelik, Ahmet. “Using Apriori Data Mining Method in COVID-19 Diagnosis”. Journal of Engineering Technology and Applied Sciences, vol. 5, no. 3, 2020, pp. 121-3, doi:10.30931/jetas.857665.
Vancouver Çelik A. Using Apriori Data Mining Method in COVID-19 Diagnosis. JETAS. 2020;5(3):121-3.