Data Mining for Medical Systems: A Review

Data mining is a growing area of research that intersects with many disciplines such as Artificial Intelligence (AI), databases, statistics, visualization, and high-performance and parallel computing. The goal of data mining is to turn data that are facts, numbers, or text which can be processed by a computer into knowledge. Nowadays, the reliance of health care on data is increasing. Therefore, this paper aims to allow the readers to understand about data mining and its importance in

[1]  Mehmed Kantardzic,et al.  Data Mining: Concepts, Models, Methods, and Algorithms , 2002 .

[2]  Hong Qiao,et al.  Comparing data mining methods with logistic regression in childhood obesity prediction , 2009, Inf. Syst. Frontiers.

[3]  David F. Lobach,et al.  Medical data mining: knowledge discovery in a clinical data warehouse , 1997, AMIA.

[4]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .

[5]  Norman D. Black,et al.  Evaluation of Outcome Prediction for a Clinical Diabetes Database , 2004, KELSI.

[6]  Eva Pagano,et al.  Using Data Mining Techniques in Monitoring Diabetes Care. The Simpler the Better? , 2011, Journal of Medical Systems.

[7]  Ayse Basar Bener,et al.  ROC Based Evaluation and Comparison of Classifiers for IVF Implantation Prediction , 2009, eHealth.

[8]  Ian H. Witten,et al.  Data mining: practical machine learning tools and techniques, 3rd Edition , 1999 .

[9]  Ashok N. Srivastava,et al.  Data Mining: Concepts, Models, Methods, and Algorithms , 2005, J. Comput. Inf. Sci. Eng..

[10]  A Linos,et al.  Data mining: a new technique in medical research. , 2005, Hormones.

[11]  Erik Strumbelj,et al.  Explanation and reliability of prediction models: the case of breast cancer recurrence , 2010, Knowledge and Information Systems.

[12]  Jianxin Chen,et al.  A Comparison of Four Data Mining Models: Bayes, Neural Network, SVM and Decision Trees in Identifying Syndromes in Coronary Heart Disease , 2007, ISNN.

[13]  Chabane Djeraba Data mining from multimedia , 2007, Int. J. Parallel Emergent Distributed Syst..

[14]  Haitao Cheng,et al.  Data Mining for Protein Secondary Structure Prediction , 2009 .

[15]  Ilias Maglogiannis,et al.  An intelligent system for automated breast cancer diagnosis and prognosis using SVM based classifiers , 2009, Applied Intelligence.

[16]  Adel Said Elmaghraby,et al.  Data Mining from Multimedia Patient Records , 2006 .

[17]  Qi Luo,et al.  Advancing Knowledge Discovery and Data Mining , 2008, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008).

[18]  Liangxiao Jiang,et al.  A Novel Bayes Model: Hidden Naive Bayes , 2009, IEEE Transactions on Knowledge and Data Engineering.

[19]  Ian H. Witten,et al.  Comprar Data Mining . Practical Machine Learning Tools and Techniques | Ian H. Witten | 9780120884070 | Morgan Kaufmann , 2008 .

[20]  Yongjian Fu,et al.  Data mining , 1997 .

[21]  Jie Wang,et al.  Combination Data Mining Methods with New Medical Data to Predicting Outcome of Coronary Heart Disease , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[22]  Nada Lavrac,et al.  Data Mining for Decision Support: An Application in Public Health Care , 2005, IEA/AIE.

[23]  Bojan Novak,et al.  Application of artificial neural networks for childhood obesity prediction , 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.