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Volumn , Issue , 2009, Pages 332-349

Mining tuberculosis data

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EID: 84880738514     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4018/978-1-60566-218-3.ch016     Document Type: Chapter
Times cited : (5)

References (23)
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  • 7
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    • Diagnosis of smear-negative pulmonary tuberculosis in peaple with hiv infection or aids in resource-constrained setting: Informing urgent policy changes
    • Getahun, H., Harrington, M., O'Brien, R., & Nunn, P. (2007). Diagnosis of smear-negative pulmonary tuberculosis in peaple with HIV infection or AIDS in resource-constrained setting: informing urgent policy changes. Lancet, 369, 2042-2049.
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    • Jianxin, C., Yanwei, X., Guangcheng, X., Jing, C., Jianqiang, Y., Dongbin, Z., & Jie, W. (2007). A Comparison of Four Data Mining Models: Bayes, Neural Network, SVM and Decision Trees in Identifying Syndromes in Coronary Heart Disease. Lecture Notes in Computer Science. Advances in Neural Networks, 4491, 1274-1279.
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    • Jianxin, C.1    Yanwei, X.2    Guangcheng, X.3    Jing, C.4    Jianqiang, Y.5    Dongbin, Z.6    Jie, W.7
  • 10
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    • Developing an antituberculosis compounds database and data mining in the search of motif responsible for the activity of a diverse class of antituberculosis agents
    • Prakash, O., & Ghosh, I. (2006). Developing an Antituberculosis Compounds Database and Data Mining in the Search of Motif Responsible for the Activity of a Diverse Class of Antituberculosis Agents. Journal of Chemical Information and Modeling, 46(1), 17-23.
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