Predicting syndrome by NEI specifications: A comparison of five data mining algorithms in coronary heart disease

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4689 LNBI, Issue , 2007, Pages 129-135

  Chen, Jianxin ^a   Xi, Guangcheng ^a   Xing, Yanwei ^b   Chen, Jing ^a   Wang, Jie ^b  

^a INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^b INSTITUTE OF CHINESE MATERIA MEDICA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ANGIOGRAPHY; CARDIOVASCULAR SYSTEM; DATA MINING; EPIDEMIOLOGY; NEURAL NETWORKS;

BAYESIAN MODELS; CORONARY ARTERY ANGIOGRAPHY; CORONARY HEART DISEASE; SYNDROME;

DISEASES;

EID: 38049130260     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74771-0_15     Document Type: Conference Paper

References (13)

1. World Health Organization.: World Health statistics Annual. Geneva, Switzerland, World Health Organization (2006)
2. Normile, D.: The new face of Traditional Chinese Medicine. Science 299, 188-190 (2003)
3. Xue, T.H., Roy, R.: Studying Traditional Chinese Medicine. Science 300, 740-741 (2003)
4. Roth, J., LeRoith, D., et al.: The evolutionary origins of hormones, neurotransmitters, and other extracellular chemical messengers: implications for mammalian biology. The New England Journal of Medicine 306, 523-527 (2006)
5. Brudzewski, K., Osowski, S., Markiewicz, T.: Classification of milk by means of an electronic nose and SVM neural network. Sensors and Actuators B 98, 291-298 (2004)
6. Keerth, S., Shevade, K., et al.: Improvements to Platt's SMO Algorithm for SVM classifier design. Neural Computation 13, 637-649 (2001)
7. Quinlan, R.: C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA (1993)
8. Huang, C.L., Shih, H.C., Chao, C.Y.: Semantic Analysis of Soccer Video Using Dynamic Bayesian Network. IEEE Transactions on Multimedia 8, 749-760 (2006)
9. Witten, I.H., FrankMichalewicz, E.Z.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)
10. Delen, D., Walker, G., Kadam, A.: Predicting breast cancer survivability. Artif. Intell. Med. 34, 113-127 (2005)
11. Vapnik, K.: Statistical learning theory. Wiley, New York (1998)
12. Graf, A., Wichmann, F., Bulthoff, H., et al.: Classification of faces in man and machine. Neural Computation 18, 143-165 (2006)
13. Hastie, T., Tibshirani, R., Friedman, J.: The elements of statistical learning. Springer, New York (2001)