Elizabeth S. Burnside
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
21
Venues
10
Active years
1999–2018
Best venue rank
A*
Where they publish
Papers
21 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2018 | AMIA | Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants. | Shara Feld, Kaitlin M. Woo, Roxana Alexandridis, Yirong Wu, Jie Liu, Peggy L. Peissig, Adedayo A. Onitilo, Jennifer Cox, David Page, Elizabeth S. Burnside |
| 2016 | CBMS | A Speech-to-Text Interface for MammoClass. | Ricardo Sousa Rocha, Pedro Ferreira, Ins de Castro Dutra, Ricardo Cruz-Correia, Rogerio Salvini, Elizabeth S. Burnside |
| 2015 | ICMLA | SkILL - A Stochastic Inductive Logic Learner. | Joana Crte-Real, Theofrastos Mantadelis, Ins de Castro Dutra, Ricardo Rocha, Elizabeth S. Burnside |
| 2014 | AISTATS | Learning Heterogeneous Hidden Markov Random Fields. | Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page |
| 2014 | AMIA | A Novel Method to Assess Incompleteness of Mammography Report Content. | Francisco Gimenez, Yirong Wu, Elizabeth S. Burnside, Daniel L. Rubin |
| 2014 | AMIA | Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. | Yirong Wu, Jie Liu, David Page, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside |
| 2014 | ICML | Multiple Testing under Dependence via Semiparametric Graphical Models. | Jie Liu, Chunming Zhang, Elizabeth S. Burnside, David Page |
| 2014 | ICMLA | Expert Bayes: Automatically Refining Manually Built Bayesian Networks. | Ezilda Almeida, Pedro Ferreira, Tiago T. V. Vinhoza, Ins de Castro Dutra, Paulo Vinicius Koerich Borges, Yirong Wu, Elizabeth S. Burnside |
| 2013 | AMIA | Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. | Jie Liu, David Page, Houssam Nassif, Jude W. Shavlik, Peggy L. Peissig, Catherine A. McCarty, Adedayo A. Onitilo, Elizabeth S. Burnside |
| 2013 | AMIA | Using Multidimensional Mutual Information to Prioritize Mammographic Features for Breast Cancer Diagnosis. | Yirong Wu, David J. Vanness, Elizabeth S. Burnside |
| 2013 | HealthCom | Using machine learning to identify benign cases with non-definitive biopsy. | Finn Kuusisto, Ins de Castro Dutra, Houssam Nassif, Yirong Wu, Molly E. Klein, Heather B. Neuman, Jude W. Shavlik, Elizabeth S. Burnside |
| 2013 | ILP | Uplift Modeling with ROC: An SRL Case Study. | Houssam Nassif, Finn Kuusisto, Elizabeth S. Burnside, Jude W. Shavlik |
| 2012 | AMIA | Logical Differential Prediction Bayes Net, improving breast cancer diagnosis for older women. | Houssam Nassif, Yirong Wu, David Page, Elizabeth S. Burnside |
| 2012 | UAI | Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies. | Jie Liu, Chunming Zhang, Catherine A. McCarty, Peggy L. Peissig, Elizabeth S. Burnside, David Page |
| 2009 | ICDM | Information Extraction for Clinical Data Mining: A Mammography Case Study. | Houssam Nassif, Ryan W. Woods, Elizabeth S. Burnside, Mehmet Ayvaci, Jude W. Shavlik, David Page |
| 2009 | ILP | Boosting First-Order Clauses for Large, Skewed Data Sets. | Louis Oliphant, Elizabeth S. Burnside, Jude W. Shavlik |
| 2007 | IJCAI | Change of Representation for Statistical Relational Learning. | Jesse Davis, Irene M. Ong, Jan Struyf, Elizabeth S. Burnside, David Page, Vtor Santos Costa |
| 2005 | AMIA | Knowledge Discovery from Structured Mammography Reports Using Inductive Logic Programming. | Elizabeth S. Burnside, Jesse Davis, Vtor Santos Costa, Ins de Castro Dutra, Charles E. Kahn Jr., Jason Fine, David Page |
| 2005 | IJCAI | View Learning for Statistical Relational Learning: With an Application to Mammography. | Jesse Davis, Elizabeth S. Burnside, Ins de Castro Dutra, David Page, Raghu Ramakrishnan, Vtor Santos Costa, Jude W. Shavlik |
| 2000 | AMIA | A Bayesian network for mammography. | Elizabeth S. Burnside, Daniel L. Rubin, Ross D. Shachter |
| 1999 | AMIA | Representing the Digital Anatomist Foundational Model as a Protege Ontology. | Jin S. Hahn, Elizabeth S. Burnside, James F. Brinkley, Cornelius Rosse, Mark A. Musen |