EHR-based Phenotyping Project
Neuroimage-based Phenotyping Project
Epigenome-based Phenotyping Project
Transcriptome-based Phenotyping Project
Phenotype Models for Breast Cancer Screening Project
Stochastic Modeling Lab
Low-dimensional Representations Lab
Data Management Lab
Value of Information Lab
Software Engineering and High-Throughput Computing Core
Bioethics Core
Recent CPCP Publications
Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants. Feld S, Woo K, Alexandridis R, Wu Y, Liu J, Peissig P, Onitilo A, Cox J, Page D, Burnside E. Proceedings of the AMIA Annual Symposium, 2018
Privacy-preserving ridge regression with only linearly-homomorphic encryption. Giacomelli I , Jha S, Joye M, Page CD, Yoon K. Proceedings of Applied Cryptography & Network Security (ACNS), 2018
Opportunities and obstacles for deep learning in biology and medicine. Ching T et al. Journal of the Royal Society Interface 15:20170387, 2018
MatchCatcher: A debugger for blocking in entity matching. Li H, Konda P, Suganthan P, Doan A, Snyder B, Park Y, Krishnan G, Deep R, Raghavendra V. Proceedings of International Conference on Extending Database Technology (EDBT), 2018
Utility of genetic testing in addition to mammography for determining risk of breast cancer depends on patient age. Feld S, Fan J, Yuan M, Wu Y, Woo K, Alexandridis R, Burnside E. Proceedings of the AMIA Informatics Summit, 2018
Using machine learning algorithms to predict risk for development of calciphylaxis in patients with chronic kidney disease. Kleiman R, LaRose E, Badger J, Page D, Caldwell M, Clay J, Peissig P. Proceedings of the AMIA Informatics Summit, 2018
Quantifying predictive capability of electronic health records for the most harmful breast cancer. Wu Y, Fan J, Peissig P, Berg R, Tafti P, Yin J, Yuan M, Page D, Cox J, Burnside E. Proceedings of SPIE Medical Imaging, 2018
Applying family analyses to electronic health records to facilitate genetic research. Huang X, Elston RC, Rosa GJ, Mayer J, Ye Z, Kitchner T, Brilliant MH, Page D, Hebbring SJ. Bioinformatics 34(4):635–642, 2018
Statistical tests and identifiability conditions for pooling and analyzing multisite datasets. Zhou HH, Singh V, Johnson SC, Wahba G, and the Alzheimer’s Disease Neuroimaging Initiative. Proceedings of the National Academy of Sciences USA, 2018