Araştırma Makalesi
Yıl 2019,
Cilt: 20 Sayı: 1, 410 - 419, 31.05.2019
Öz
Bu çalışmada, hastane kayıtlarındaki
veriler, veri madenciliği tekniği ile analiz edilerek başvurulan hastane
servisleri arasında birliktelik kurallarının olup olmadığı araştırılmaya
çalışılmıştır. Bu amaçla 31.552 hastaya ait veriler işlenerek, Birliktelik
Kuralları Madenciliği yapılmıştır. Yapılan çalışma sonucunda %75 güven
seviyesinin üstünde 58 kural üretilebilmiştir. Üretilen bu kuralların hastane
yöneticilerinin kararlarına katkı sağlayacağı değerlendirilmektedir.
Anahtar Kelimeler
Kaynakça
- Agrawal, R., & Srikant, R. (1994), Fast algorithms for mining association rules. In Proceedings of the 20th international conference on very large data bases, Santiago, Chile. Citeseer, :487–499.
- Arora, Jyoti; Bhalla, Nidhi and Rao,Sanjeev (2013), ‘A Review On Association Rule Mining Algorithms’ International Journal of Innovative Research in Computer and Communication Engineering 1.5: 1246-1251.
- Bose, I., Chun, L. A.,Yue, L. V. W., Ines, L. H. W. and Helen, W. O. L. (2009), ‘Business Data Warehouse: The Case of Wal-Mart’, Data Mining Applications for Empowering Knowledge Societies, Ed. Hakikur Rahman, Information Science Reference, :189-198
- Brossette, Stephen E., Sprague, Alan P., Hardin, J. Mıchael, Waites, Ken B., Jones, Warren T., Moser, Stephen A., (1998), Data Mining İn Hospital Infection Control And Public Health Surveillance, Journal Of The American Medical Informatics Association Volume 5 Number 4 Jul / Aug 1998,:.373-381
- Fayyad, Usama, Gregory Piatetsky-Shapiro, and Padhraic Smyth (1996). ‘From data mining to knowledge discovery in databases’ AI magazine 17.3: 37-54.Giudici, Paolo and Figini, Silvia (2009), Applied Data Mining For Business and Industry,Second Edition, Wiley Publicition, West Sussex.
- Han, Jiawei, and Micheline Kamber (2006). Data Mining, Southeast Asia Edition: Concepts and Techniques. Morgan Kaufmann.
- Ilayaraja, M. & Meyyappan, Thiru (2013), Mining Medical Data To Identify Frequent Diseases Using Apriori Algorithm, Proceedings Of The 2013 International Conference On Pattern Recognition, Informatics And Mobile Engineering, February 21-22, :194-199
- Isken, Mark W. and Rajagopalan, Balaji (2002), Data Mining to Support Simulation Modeling of Patient Flow in Hospitals, Journal of Medical Systems, Vol. 26, No. 2, April 2002, :179-197
- Jain, Yogendra Kumar, Vinod Kumar Yadav, and Geetika S. Panday. (2011) ‘An Efficient Association Rule Hiding Algorithm for Privacy Preserving Data Mining’ International Journal on Computer Science and Engineering 3.7 : 2792-2798.
- Kantardzic, Mehmed (2003) Data Mining: Concepts, Models, Methods, and Algorithms, John Wiley & Sons J. B. Speed Scientific School, University of Louisville IEEE Computer Society.
- Krishnaiah,V., Narsimha, G. & Chandra, N. S. (2013), A Study On Clınıcal Predictıon Using Data Mining Techniques, International Journal of Computer Science Engineering and Information Technology Research (IJCSEITR) ISSN 2249-6831 Vol. 3, Issue 1:239-248.
- Lakshmi K.S. , Vadivu, G. (2017), Extracting Association Rules from Medical Health Records Using Multi-Criteria Decision Analysis, 7th International Conference on Advances in Computing & Communications, ICACC-2017, 22-24 August 2017, Procedia Computer Science 115 (2017) pp. 290–295, Elsevier, Cochin, India
- Nahar J., Imam T., Tickle KS., Chen YP (2013), Association Rule Mining To Detect Factors Which Contribute To Heart Disease in Males And Females, Expert Systems with Applications 40 (2013) 1086–1093
- Nisbet, Robert, John Elder IV, and Gary Miner, (2009), Handbook of statistical analysis and data mining applications. Elsevier Inc, Burlington.
- Patil, B. M., Joshi,R. C. & Toshniwal, D. (2010), Association rule for classification of type -2 diabetic patients, 2010 Second International Conference on Machine Learning and Computing, 978-0-7695-3977-5/10 © 2010 IEEE, DOI 10.1109/ICMLC.2010.67, IEEE Computer Society
- Rokach, Lior and Maimon, Oded, (2008), Data Mining with Decision Trees: Theory and Applications, World Scientific New Jersey.
- Stiloul, S.& Bamidis, P.D.& Maglaveras,N.& Pappas, C.(2001), Mining Association Rules from Clinical Databases: An Intelligent Diagnostic Process in Healthcare, MEDINFO 2001,V. Patel et al. (Eds),Amsterdam: IOS Press,:1399-1403
- Taş, Yusuf (2018), Birliktelik Kuralları Madenciliği Ve Bir Uygulama, Cumhuriyet Üniversitesi, Sosyal Bilimler Enstitüsü, Yüksek Lisans Tezi, Sivas
- Tsumoto, Shusaku, Hirano, Shoji, Tsumoto, Yuko (2011), Information Reuse in Hospital Information Systems: A Data Mining Approach, IEEE IRI 2011, August 3-5, 2011, Las Vegas, Nevada,:172-176
- Webb, G.,I. (2003). Association Rules. In Nong Ye (Edt.), The Handbook Of data Mining (pp. 27-28). New Jersey: Lawrence Erlbaum Associates,Inc.
- Wu, Tong and Li, Xiangyang (2003), ‘Data Storage and Management’, The Handbook of Data Mining, Ed. Nong Ye, New Jersey: Lawrence Erlbaum Associates, Inc.: 393-407.
Toplam 21 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 31 Mayıs 2019 |
| Gönderilme Tarihi | 25 Şubat 2019 |
| Yayımlandığı Sayı | Yıl 2019Cilt: 20 Sayı: 1 |
Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi Creative Commons Atıf-GayriTicari 4.0 Uluslararası Lisansı (CC BY NC) ile lisanslanmıştır.