Elizabeth S. Burnside

	2012
13		Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, C. David Page Jr.: High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. Journal of Machine Learning Research - Proceedings Track 22: 712-721 (2012)
	2011
12		Pedro Ferreira, Nuno A. Fonseca, Inês de Castro Dutra, Ryan W. Woods, Elizabeth S. Burnside: Predicting Malignancy from Mammography Findings and Surgical Biopsies. BIBM 2011: 339-344
11		Pedro Ferreira, Inês de Castro Dutra, Nuno A. Fonseca, Ryan W. Woods, Elizabeth S. Burnside: Studying the Relevance of Breast Imaging Features. HEALTHINF 2011: 337-342
	2010
10		Houssam Nassif, David Page, Mehmet Ayvaci, Jude W. Shavlik, Elizabeth S. Burnside: Uncovering age-specific invasive and DCIS breast cancer rules using inductive logic programming. IHI 2010: 76-82
9		Ryan W. Woods, Louis Oliphant, Kazuhiko Shinki, David Page, Jude W. Shavlik, Elizabeth S. Burnside: Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer. J. Digital Imaging 23(5): 554-561 (2010)
8		Jagpreet Chhatwal, Oguzhan Alagöz, Elizabeth S. Burnside: Optimal Breast Biopsy Decision-Making Based on Mammographic Features and Demographic Factors. Operations Research 58(6): 1577-1591 (2010)
	2009
7		Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page: Information Extraction for Clinical Data Mining: A Mammography Case Study. ICDM Workshops 2009: 37-42
6		Louis Oliphant, Elizabeth S. Burnside, Jude W. Shavlik: Boosting First-Order Clauses for Large, Skewed Data Sets. ILP 2009: 166-177
	2007
5		Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vítor Santos Costa: Change of Representation for Statistical Relational Learning. IJCAI 2007: 2719-2726
	2005
4		Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Vítor Santos Costa: An Integrated Approach to Learning Bayesian Networks of Rules. ECML 2005: 84-95
3		Jesse Davis, Elizabeth S. Burnside, Inês de Castro Dutra, David Page, Raghu Ramakrishnan, Vítor Santos Costa, Jude W. Shavlik: View Learning for Statistical Relational Learning: With an Application to Mammography. IJCAI 2005: 677-683
	2004
2		Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter: Improving a Bayesian network's ability to predict the probability of malignancy of microcalcifications on mammography. CARS 2004: 1021-1026
1		Yue Pan, Elizabeth S. Burnside: The effects of training parameters on learning a probabilistic expert system for mammography. CARS 2004: 1027-1032

Coauthor Index

1	Oguzhan Alagöz	[8]
2	Mehmet Ayvaci	[7] [10]
3	Jagpreet Chhatwal	[8]
4	Vítor Santos Costa	[3] [4] [5]
5	Jesse Davis	[3] [4] [5]
6	Inês de Castro Dutra	[3] [4] [11] [12]
7	Pedro Ferreira	[11] [12]
8	Nuno A. Fonseca	[11] [12]
9	Jie Liu	[13]
10	Catherine A. McCarty	[13]
11	Houssam Nassif	[7] [10]
12	Louis Oliphant	[6] [9]
13	Irene M. Ong	[5]
14	C. David Page Jr. (David Page)	[3] [4] [5] [7] [9] [10] [13]
15	Yue Pan	[1]
16	Peggy L. Peissig	[13]
17	Raghu Ramakrishnan	[3]
18	Daniel L. Rubin	[2]
19	Ross D. Shachter	[2]
20	Jude W. Shavlik	[3] [6] [7] [9] [10]
21	Kazuhiko Shinki	[9]
22	Jan Struyf	[5]
23	Ryan W. Woods	[7] [9] [11] [12]
24	Chunming Zhang	[13]

Colors in the list of coauthors

Last update Sun May 27 04:04:01 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page