Breast cancer risk score: a data mining approach to improve readability
暂无分享,去创建一个
Laurent Brisson | Philippe Lenca | Emilien Gauthier | Stéphane Ragusa | S. Ragusa | P. Lenca | Laurent Brisson | E. Gauthier
[1] Karla Kerlikowske,et al. Prospective breast cancer risk prediction model for women undergoing screening mammography. , 2006, Journal of the National Cancer Institute.
[2] K. Kerlikowske,et al. Breast Cancer Surveillance Consortium: a national mammography screening and outcomes database. , 1997, AJR. American journal of roentgenology.
[3] M. Kallergi,et al. Simulation model of mammographic calcifications based on the American College of Radiology Breast Imaging Reporting and Data System, or BIRADS. , 1998, Academic radiology.
[4] José Antonio Gómez-Ruiz,et al. A combined neural network and decision trees model for prognosis of breast cancer relapse , 2003, Artif. Intell. Medicine.
[5] James P. Egan,et al. Signal detection theory and ROC analysis , 1975 .
[6] J. Kaprio,et al. Environmental and heritable factors in the causation of cancer--analyses of cohorts of twins from Sweden, Denmark, and Finland. , 2000, The New England journal of medicine.
[7] M. Sporn. The war on cancer , 1996, The Lancet.
[8] JapkowiczNathalie,et al. The class imbalance problem: A systematic study , 2002 .
[9] M. Gail,et al. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. , 1989, Journal of the National Cancer Institute.
[10] B. Stewart,et al. World Cancer Report , 2003 .
[11] Tom Fawcett,et al. An introduction to ROC analysis , 2006, Pattern Recognit. Lett..
[12] Fh collaborative teams. Mammographic surveillance in women younger than 50 years who have a family history of breast cancer: tumour characteristics and projected effect on mortality in the prospective, single-arm, FH01 study. , 2010, The Lancet. Oncology.
[13] Stefano Calza,et al. Gail model for prediction of absolute risk of invasive breast cancer: independent evaluation in the Florence-European Prospective Investigation Into Cancer and Nutrition cohort. , 2006, Journal of the National Cancer Institute.
[14] Ralescu Anca,et al. ISSUES IN MINING IMBALANCED DATA SETS - A REVIEW PAPER , 2005 .
[15] Pedro M. Domingos. MetaCost: a general method for making classifiers cost-sensitive , 1999, KDD '99.
[16] Peter E. Hart,et al. Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.
[17] Joydeep Ghosh,et al. Generative Oversampling for Mining Imbalanced Datasets , 2007, DMIN.
[18] Hiroshi Tanaka,et al. Comparison of Seven Algorithms to Predict Breast Cancer Survival( Contribution to 21 Century Intelligent Technologies and Bioinformatics) , 2008 .
[19] Thomas Reinartz,et al. CRISP-DM 1.0: Step-by-step data mining guide , 2000 .
[20] J Benichou,et al. Validation studies for models projecting the risk of invasive and total breast cancer incidence. , 1999, Journal of the National Cancer Institute.
[21] R. Rubin. The war on cancer. , 1996, U.S. news & world report.
[22] Nathalie Japkowicz,et al. The class imbalance problem: A systematic study , 2002, Intell. Data Anal..
[23] Foster J. Provost,et al. Learning When Training Data are Costly: The Effect of Class Distribution on Tree Induction , 2003, J. Artif. Intell. Res..
[24] Thanh-Nghi Do,et al. Using Local Node Information in Decision Trees: Coupling a Local Labeling Rule with an Off-centered Entropy , 2008, DMIN.
[25] Zhi-Hua Zhou,et al. Exploratory Under-Sampling for Class-Imbalance Learning , 2006, ICDM.
[26] J. L. Hodges,et al. Discriminatory Analysis - Nonparametric Discrimination: Consistency Properties , 1989 .