Post-Operative Patients Analysis using Data Mining Techniques
Anjana Menon1, Swathi R2, M Soumya Krishnan3
1Anjana Menon, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
2Swathi R, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
3M Soumya Krishnan, Department of Computer Science and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham, Kochi, India.
Manuscript received on 12 April 2019 | Revised Manuscript received on 17 May 2019 | Manuscript published on 30 May 2019 | PP: 260-264 | Volume-8 Issue-1, May 2019 | Retrieval Number: A3080058119/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The post-operative patient analysis begins immediately after the surgery. The post-operative care depends on both the type of surgery and the previous health history. With the help of this analysis we can find if there exist any complications or not. In this paper we are analyzing the data of post-Operative patients and we are identifying the state of the patient using J48 – a Data Mining Approach. After that, we are comparing various classification techniques in data mining and predicting their accuracy for post-operative patients data set. We are comparing Naïve Bayesian, SMO, LWL, J48 classifiers using performance measures like Receiver Operating Characteristic), Root mean squared Error, Kappa statistics and Mean Absolute Error using WEKA tool. Different Techniques in Data Mining could be used for the extraction of data from large data sources. Data Mining Approaches can be used in several fields like Medicine, Education, Fraud Detection, Marketing etc.
Keywords: Data Mining, J48, Naïve Bayesian, WEKA
Scope of the Article: Data Mining