Ali, K. M. and M. J. Pazzani. On the link between error correlation and error reduction in decision tree ensembles. Technical Report ICS-UCI, 1995.
Berg, W. A., J. D. Blume, J. B. Cormack, E. B. Mendelson, et al. Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer. JAMA 299(18):2151–2163, 2008.
Bilik, I., J. Tabrikian, and A. Cohen. GMM-based target classification for ground surveillance Doppler radar. IEEE Trans. Aerosp. Electron. Syst. 42(1):267–278, 2006.
Bishop, C. M. Neural Networks for Pattern Recognition. Oxford: Oxford University Press, 1995.
Burges, C. J. C. A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Discov. 2:121–167, 1998.
Cao, J., M. Ahmadi, and M. Shridhar. Recognition of handwritten numerals with multiple feature and multistage classifier. Pattern Recognit. 28(2):153–160, 1995.
Chaundhary, S. S., R. K. Mishra, A. Swarup, and J. M. Thomas. Dielectric properties of breast carcinoma and surrounding tissues. IEEE Trans. Biomed. Eng. 35:257–263, 1988.
Cho, S. B., and J. H. Kim. Combining multiple neural networks by fuzzy integral for robust classification. IEEE Trans. Syst. Man Cybern. 25(2):380–384, 1995.
Denisov, D. A., and A. K. Dudkin. Model-based chromosome recognition via hypotheses construction/verification. Pattern Recognit. Lett. 15(3):299–307, 1994.
Fairhurst, M. C., and H. M. S. A. Wahab. An interactive two-level architecture for a memory network pattern classifier. Pattern Recognit. Lett. 10(4):211–215, 1989.
Fenton, J. J., J. Egger, P. A. Carney, G. Cutter, et al. Reality check: perceived versus actual performance of community mammographers. Am. J. Roentgenol. 187:42–46, 2006.
Franco, A., and L. Nanni. Fusion of classifiers for illumination robust face recognition. Expert Syst. Appl. 36:8946–8954, 2009.
Franke, J. and E. Mandler. A comparison of two approaches for combining the votes of cooperating classifiers. In: Proc. 11th IAPR Int’l Conf. Pattern Recognition, Conf. B: Pattern Recognition Methodology and Systems, 1992, pp. 611–614.
Fricke, H., and S. Morse. The electric capacity of tumors of the breast. J. Cancer Res. 16:310–376, 1926.
Glickman, Y. A., O. Filo, U. Nachaliel, S. Lenington, et al. Novel EIS postprocessing algorithm for breast cancer diagnosis. IEEE Trans. Med. Imaging 21:710–712, 2002.
Gur, D., B. Zheng, S. Dhurjaty, G. Wolfe, et al. Developing and testing a multi-probe resonance electrical impedance spectroscopy system for detecting breast abnormalities. In: Proc. SPIE, San Diego, 2009, pp. 72631F-1-8.
Gur, D., B. Zheng, D. Lederman, S. Dhurjaty, et al. A support vector machine designed to identify breasts at high risk using multi-probe generated REIS signals: a preliminary assessment. In: Proc. SPIE, San Diego, 2010, pp. 7627B127-46.
Ho, T. K., J. J. Hull, and S. N. Srihari. Decision combination in multiple classifier systems. IEEE Trans. Pattern Anal. Mach. Intell. 16(1):66–75, 1994.
Holland, J. H. Adaptation in Neural and Artificial Systems. Ann Arbor, MI: University of Michigan Press, 1975.
Huang, T. S., and C. Y. Suen. Combining of multiple experts for the recognition of unconstrained handwritten numerals. IEEE Trans. Pattern Anal. Mach. Intell. 17(1):90–94, 1995.
Kerner, T. E., K. D. Paulsen, A. Hartov, et al. Electrical impedance spectroscopy of the breast: clinical imaging results in 26 subjects. IEEE Trans. Med. Imaging 21:638–645, 2002.
Kimura, F., and M. Shridhar. Handwritten numerical recognition based on multiple classifier systems. Pattern Recognit. 24(10):969–983, 1991.
Kitler, J., A. Hojjatoleslami, and T. Windeatt, Weighting factors in multiple expert fusion. In: Proc. British Machine Vision Conf., Colchester, England, 1997, pp. 41–50.
Kittler, J., M. Hatef, R. P. W. Duin, and J. Matas. On combining classifiers. IEEE Trans. PAMI 20(3):226–239, 1998.
Kriege, M., C. T. M. Brekelmans, C. Boetes, P. E. Besnard, et al. Efficacy of MRI and mammography for breast-cancer screening in women with a familial or genetic predisposition. N. Engl. J. Med. 351:427–437, 2004.
Kurzynski, M. W. On the identity of optimal strategies for multiple stage classifiers. Pattern Recognit. Lett. 10(1):39–46, 1989.
Leach, M. O., C. R. Boggis, A. K. Dixon, D. F. Easton, et al. Screening with magnetic resonance imaging and mammography of a UK population at high familiar risk of breast cancer: a prospective multicentre cohort study (MARIBS). Lancet 365:1769–1778, 2005.
Li, H., M. L. Giger, O. I. Olopade, and M. R. Chinander. Power spectral analysis of mammographic parenchymal patterns for breast cancer risk assessment. J. Digit. Imaging 21:145–152, 2008.
Malich, A., T. Fritsch, R. Anderson, T. Boehm, et al. Electrical impedance scanning for classifying suspicious breast lesions: first results. Eur. Radiol. 10:1555–1561, 2000.
Pipemo, G., G. Frei, and M. Moshitzky. Breast cancer screening by impedance measurement. Med. Biol. Eng. 2:111–117, 1990.
Pisano, E. D., C. Gatsonis, E. Hendrick, M. Yaffe, et al. Diagnostic performance of digital versus film mammography for breast cancer screening. N. Engl. J. Med. 353:1773–1783, 2005.
Poplack, S. P., K. D. Paulsen, A. Hartov, P. M. Meaney, et al. Electromagnetic breast imaging: average tissue property values in women with negative clinical findings. Radiology 231:571–580, 2004.
Smith, R. A. Breast cancer screening among women younger than age 50: a current assessment of the issues. CA Cancer J. Clin. 50:312–336, 2000.
Stojadinovic, A., O. Moskovitz, G. Gallimidi, et al. Prospective study of electrical impedance scanning for identifying young women at risk for breast cancer. Breast Cancer Res. Treat. 97:179–189, 2006.
Stojadinovic, A., A. Nissan, and Z. Gallimidi. Electrical impedance scanning for the early detection of breast cancer in young women: preliminary results of a multicenter prospective clinical trial. J. Clin. Oncol. 23:2703–2715, 2005.
Stojadinovic, A., A. Nissan, and C. D. Shriver. Electrical impedance scanning as a new breast cancer risk stratification tool for young women. J. Surg. Oncol. 97:112–120, 2008.
Sumkin, J., B. Zheng, M. Gruss, J. Drescher, et al. Assembling a prototype resonance electrical impedance spectroscopy system for breast tissue signal detection: preliminary assessment. In: Proc. SPIE, 2008, pp. 691716-1-8.
Sumkin, J. H., A. Stojadinovic, and M. Huerbin, Impedance measurements for early detection of breast cancer in younger women: a preliminary assessment. In: Proc. SPIE, 2003, pp. 197–203.
Tang, K. S., K. F. Man, S. Kwong, and Q. H. He. Genetic algorithms and their applications. IEEE Signal Process. Mag. 13(6):22–37, 1996.
Tulyakov, S., S. Jaeger, V. Govindaraju, and D. Doermann. Review of classifier combination methods. In: Studies in Computational Intelligence (SCI), Vol. 90. Berlin, Heidelberg: Springer, 2008, pp. 361–386.
Verbeek, J. J., N. Vlassis, and B. Kröse. Efficient greedy learning of Gaussian mixture models. Neural Comput. 15(2):468–485, 2003.
Vlassis, N., and A. Likas. A greedy EM algorithm for Gaussian mixture learning. Neural Proc. Lett. 15:77–87, 2002.
Warner, E., D. B. Plewes, K. A. Hill, P. A. Causer, et al. Surveillance of BRCA1 and BRCA2 mutation carriers with magnetic resonance imaging, ultrasound, mammography, and clinical breast examination. J. Am. Med. Assoc. 292:1317–1325, 2004.
WHO, Annual report of the World Health Organization, fact sheet no. 297: Cancer, 2009.
Wolfe, J. N. Breast patterns as an index of risk for developing breast cancer. Am. J. Roentgenol. 126:1130–1139, 1976.
Wolpert, D. H. Stacked generalization. Neural Netw. 5(2):241–260, 1992.
Xu, L., A. Krzyzak, and C. Y. Suen. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans. Syst. Man Cybern. 22(3):418–435, 1992.
Zheng, B., M. L. Zuley, J. H. Sumkin, V. J. Catullo, et al. Detection of breast abnormalities using a prototype resonance electrical impedance spectroscopy system: a preliminary study. Med. Phys. 35:3041–3048, 2008.
Zhou, J. Y., and T. Pavlidis. Discrimination of characters by a multi-stage process. Pattern Recognit. 27(11):1539–1549, 1994.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4