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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

103 related items for PubMed ID: 19150588

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  • 2. The prediction of cardiovascular disease based on trace element contents in hair and a classifier of boosting decision stumps.
    Tan C, Chen H, Xia C.
    Biol Trace Elem Res; 2009; 129(1-3):9-19. PubMed ID: 19066736
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  • 4. Entropy and complexity measures for EEG signal classification of schizophrenic and control participants.
    Sabeti M, Katebi S, Boostani R.
    Artif Intell Med; 2009 Nov; 47(3):263-74. PubMed ID: 19403281
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  • 6. Prediction of type-2 diabetes based on several element levels in blood and chemometrics.
    Chen H, Tan C.
    Biol Trace Elem Res; 2012 Jun; 147(1-3):67-74. PubMed ID: 22201046
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  • 7. Using Chou's pseudo amino acid composition based on approximate entropy and an ensemble of AdaBoost classifiers to predict protein subnuclear location.
    Jiang X, Wei R, Zhao Y, Zhang T.
    Amino Acids; 2008 May; 34(4):669-75. PubMed ID: 18256886
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  • 8. AdaBoost-based algorithm for network intrusion detection.
    Hu W, Hu W, Maybank S.
    IEEE Trans Syst Man Cybern B Cybern; 2008 Apr; 38(2):577-83. PubMed ID: 18348941
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  • 11. Application of boosting classification and regression to modeling the relationships between trace elements and diseases.
    Tan C, Chen H, Zhu W.
    Biol Trace Elem Res; 2010 May; 134(2):146-59. PubMed ID: 19629402
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  • 13. Boosting random subspace method.
    García-Pedrajas N, Ortiz-Boyer D.
    Neural Netw; 2008 Nov; 21(9):1344-62. PubMed ID: 18272334
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  • 16. Study of the feasibility of distinguishing cigarettes of different brands using an Adaboost algorithm and near-infrared spectroscopy.
    Tan C, Li M, Qin X.
    Anal Bioanal Chem; 2007 Sep; 389(2):667-74. PubMed ID: 17641880
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  • 17. Accuracy and prognostic impact of a vessel invasion grading system for stage IA non-small cell lung cancer.
    Hashizume S, Nagayasu T, Hayashi T, Hidaka S, Tsuchiya T, Tagawa T, Yamasaki N, Furukawa K, Matsumoto K, Miyazaki T.
    Lung Cancer; 2009 Sep; 65(3):363-70. PubMed ID: 19157635
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  • 20. Predicting the outcome of patients with subarachnoid hemorrhage using machine learning techniques.
    de Toledo P, Rios PM, Ledezma A, Sanchis A, Alen JF, Lagares A.
    IEEE Trans Inf Technol Biomed; 2009 Sep; 13(5):794-801. PubMed ID: 19369161
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