An active learning based classification strategy for the minority class problem: application to histopathology annotation
暂无分享,去创建一个
Anant Madabhushi | Michael D. Feldman | Scott Doyle | John E. Tomaszeweski | James Monaco | A. Madabhushi | M. Feldman | Scott Doyle | J. Monaco | J. Tomaszeweski
[1] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[2] JapkowiczNathalie,et al. The class imbalance problem: A systematic study , 2002 .
[3] Jianzhong Li,et al. A stable gene selection in microarray data analysis , 2006, BMC Bioinformatics.
[4] Ehud Rivlin,et al. A Microscopic Telepathology System for Multiresolution Computer-Aided Diagnostics , 2006, J. Multim..
[5] Daphne Koller,et al. Active Learning for Structure in Bayesian Networks , 2001, IJCAI.
[6] Zhuowen Tu,et al. Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.
[7] David A. Cohn,et al. Active Learning with Statistical Models , 1996, NIPS.
[8] Edward H. Adelson,et al. The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..
[9] Purang Abolmaesumi,et al. High-throughput detection of prostate cancer in histological sections using probabilistic pairwise Markov models , 2010, Medical Image Anal..
[10] Byoung-Tak Zhang,et al. AESNB: Active Example Selection with Naïve Bayes Classifier for Learning from Imbalanced Biomedical Data , 2009, 2009 Ninth IEEE International Conference on Bioinformatics and BioEngineering.
[11] Paolo Avesani,et al. Active Sampling for Knowledge Discovery from Biomedical Data , 2005, PKDD.
[12] John Meyer,et al. Grading nuclear pleomorphism on histological micrographs , 2008, 2008 19th International Conference on Pattern Recognition.
[13] J. Ross Quinlan,et al. Decision trees and decision-making , 1990, IEEE Trans. Syst. Man Cybern..
[14] Nathalie Japkowicz,et al. The class imbalance problem: A systematic study , 2002, Intell. Data Anal..
[15] Anant Madabhushi,et al. Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features , 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[16] S. Hochreiter,et al. REINFORCEMENT DRIVEN INFORMATION ACQUISITION IN NONDETERMINISTIC ENVIRONMENTS , 1995 .
[17] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[18] Gyan Bhanot,et al. Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology , 2010, IEEE Transactions on Biomedical Engineering.
[19] A. Madabhushi,et al. Histopathological Image Analysis: A Review , 2009, IEEE Reviews in Biomedical Engineering.
[20] A. Madabhushi,et al. Integrated diagnostics: a conceptual framework with examples , 2010, Clinical chemistry and laboratory medicine.
[21] Anant Madabhushi,et al. A Class Balanced Active Learning Scheme that Accounts for Minority Class Problems : Applications to Histopathology , 2009 .
[22] Ishwar K. Sethi,et al. Confidence-based active learning , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[23] Anant Madabhushi,et al. Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis , 2010, PRIB.
[24] André Carlos Ponce de Leon Ferreira de Carvalho,et al. Applying One-Sided Selection to Unbalanced Datasets , 2000, MICAI.
[25] BMC Bioinformatics , 2005 .
[26] Etienne Barnard,et al. Data characteristics that determine classifier performance , 2006 .
[27] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[28] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[29] H. Sebastian Seung,et al. Selective Sampling Using the Query by Committee Algorithm , 1997, Machine Learning.
[30] K. Vijay-Shanker,et al. Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets , 2009, NAACL.
[31] Philipp Koehn,et al. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL) , 2007 .
[32] H. Sebastian Seung,et al. Query by committee , 1992, COLT '92.
[33] Robert M. Haralick,et al. Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..
[34] David A. Cohn,et al. Improving generalization with active learning , 1994, Machine Learning.
[35] Gyan Bhanot,et al. Expectation–Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology , 2010, IEEE Transactions on Biomedical Engineering.
[36] B. S. Manjunath,et al. Texture Features for Browsing and Retrieval of Image Data , 1996, IEEE Trans. Pattern Anal. Mach. Intell..
[37] Anant Madabhushi,et al. A Boosted Bayesian Multiresolution Classifier for Prostate Cancer Detection From Digitized Needle Biopsies , 2012, IEEE Transactions on Biomedical Engineering.
[38] Jingbo Zhu,et al. Active Learning for Word Sense Disambiguation with Methods for Addressing the Class Imbalance Problem , 2007, EMNLP.
[39] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[40] Foster Provost,et al. The effect of class distribution on classifier learning: an empirical study , 2001 .