Study of Effect of Drug Lexicons on Medication Extraction from Electronic Medical Records. - E. Sirohi; Peggy L. Peissig (Pacific Symposium on Biocomputing, 2005)

An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records. - Jonathan S. Schildcrout; Melissa A. Basford; Jill M. Pulley; Daniel R. Masys; Dan M. Roden; Deede Wang; Christopher G. Chute; Iftikhar J. Kullo; David Carrell; Peggy L. Peissig; Abel N. Kho; Joshua C. Denny (J. Biomed. Informatics, 2010)

Identifying Adverse Drug Events by Relational Learning. - David Page; Vítor Santos Costa; Sriraam Natarajan; Aubrey Barnard; Peggy L. Peissig; Michael Caldwell (AAAI, 2012)

Using PheWAS to Assess Pleiotropy of Genetic Risk Scores for Rheumatoid Arthritis and Coronary Artery Disease in the eMERGE Network. - Robert J. Carroll; Katherine P. Liao; Anne E. Eyler; Lisa Bastarache; Dana C. Crawford; Peggy L. Peissig; Jyotishman Pathak; David Carrell; Abel N. Kho; Rongling Li; Daniel R. Masys; Gail P. Jarvik; et al. (AMIA, 2012)

Learning to Predict Post-Hospitalization VTE Risk from EHR Data. - Emily Kawaler; Alexander G. Cobian; Peggy L. Peissig; Deanna S. Cross; Steven Yale; Mark W. Craven (AMIA, 2012)

An Evaluation of the NQF Quality Data Model for Representing Electronic Health Record Driven Phenotyping Algorithms. - William K. Thompson; Luke V. Rasmussen; Jennifer A. Pacheco; Peggy L. Peissig; Joshua C. Denny; Abel N. Kho; Aaron W. Miller; Jyotishman Pathak (AMIA, 2012)

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records. - Jeremy C. Weiss; Sriraam Natarajan; Peggy L. Peissig; Catherine A. McCarty; David Page (IAAI, 2012)

Demand-Driven Clustering in Relational Domains for Predicting Adverse Drug Events. - Jesse Davis; Vítor Santos Costa; Elizabeth Berg; David Page; Peggy L. Peissig; Michael Caldwell (ICML, 2012)

Graphical-model Based Multiple Testing under Dependence, with Applications to Genome-wide Association Studies. - Jie Liu 006; Chunming Zhang; Catherine A. McCarty; Peggy L. Peissig; Elizabeth S. Burnside; David Page (UAI, 2012)

Machine Learning for Personalized Medicine: Predicting Primary Myocardial Infarction from Electronic Health Records. - Jeremy C. Weiss; Sriraam Natarajan; Peggy L. Peissig; Catherine A. McCarty; David Page (AI Mag., 2012)

Use of diverse electronic medical record systems to identify genetic risk for type 2 diabetes within a genome-wide association study. - Abel N. Kho; M. Geoffrey Hayes; Laura Rasmussen-Torvik; Jennifer A. Pacheco; William K. Thompson; Loren L. Armstrong; Joshua C. Denny; Peggy L. Peissig; Aaron W. Miller; Wei-Qi Wei; Suzette J. Bielinski; Christopher G. Chute; et al. (J. Am. Medical Informatics Assoc., 2012)

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records. - Peggy L. Peissig; Luke V. Rasmussen; Richard L. Berg; James G. Linneman; Catherine A. McCarty; Carol Waudby; Lin Chen; Joshua C. Denny; Russell A. Wilke; Jyotishman Pathak; David Carrell; Abel N. Kho; et al. (J. Am. Medical Informatics Assoc., 2012)

Development of an optical character recognition pipeline for handwritten form fields from an electronic health record. - Luke V. Rasmussen; Peggy L. Peissig; Catherine A. McCarty; Justin Starren (J. Am. Medical Informatics Assoc., 2012)

High-Dimensional Structured Feature Screening Using Binary Markov Random Fields. - Jie Liu 006; Chunming Zhang; Catherine A. McCarty; Peggy L. Peissig; Elizabeth S. Burnside; David Page (AISTATS, 2012)

Genetic Variants Improve Breast Cancer Risk Prediction on Mammograms. - Jie Liu 006; David Page; Houssam Nassif; Jude W. Shavlik; Peggy L. Peissig; Catherine A. McCarty; Adedayo A. Onitilo; Elizabeth S. Burnside (AMIA, 2013)

Development and validation of an electronic phenotyping algorithm for chronic kidney disease. - Girish N. Nadkarni; Omri Gottesman; James G. Linneman; Herbert S. Chase; Richard L. Berg; Samira Farouk; Vaneet Lotay; Stephen B. Ellis; George Hripcsak; Peggy L. Peissig; Chunhua Weng; Rajiv Nadukuru; et al. (AMIA, 2014)

Comparing the Value of Mammographic Features and Genetic Variants in Breast Cancer Risk Prediction. - Yirong Wu; Jie Liu 006; David Page; Peggy L. Peissig; Catherine A. McCarty; Adedayo A. Onitilo; Elizabeth S. Burnside (AMIA, 2014)

Benefits of Accurate Imputations in GWAS. - Shefali S. Verma; Peggy L. Peissig; Deanna S. Cross; Carol Waudby; Murray H. Brilliant; Catherine A. McCarty; Marylyn D. Ritchie (EvoApplications, 2014)

Relational machine learning for electronic health record-driven phenotyping. - Peggy L. Peissig; Vítor Santos Costa; Michael Caldwell; Carla Rottscheit; Richard L. Berg; Eneida A. Mendonça; David Page (J. Biomed. Informatics, 2014)

Design patterns for the development of electronic health record-driven phenotype extraction algorithms. - Luke V. Rasmussen; William K. Thompson; Jennifer A. Pacheco; Abel N. Kho; David Carrell; Jyotishman Pathak; Peggy L. Peissig; Gerard Tromp; Joshua C. Denny; Justin B. Starren (J. Biomed. Informatics, 2014)

Predicting Adverse Drug Events from Electronic Medical Records. - Jesse Davis; Vítor Santos Costa; Peggy L. Peissig; Michael Caldwell; David Page (Foundations of Biomedical Knowledge Representation, 2015)

A Genome- and Phenome- Wide Study of Diverticulosis. - Yoonjung Y. Joo; Jennifer A. Pacheco; Loren L. Armstrong; William K. Thompson; Robert J. Carroll; Joshua C. Denny; Peggy L. Peissig; James G. Linneman; Jyotishman Pathak; Girish N. Nadkarni; Laura Rasmussen-Torvik; M. Geoffrey Hayes; et al. (AMIA, 2015)

Desiderata for computable representations of electronic health records-driven phenotype algorithms. - Huan Mo; William K. Thompson; Luke V. Rasmussen; Jennifer A. Pacheco; Guoqian Jiang; Richard C. Kiefer; Qian Zhu 003; Jie Xu 011; Enid N. H. Montague; David S. Carrell; Todd Lingren; Frank D. Mentch; et al. (J. Am. Medical Informatics Assoc., 2015)

CSER and eMERGE: current and potential state of the display of genetic information in the electronic health record. - Brian H. Shirts; Joseph S. Salama; Samuel J. Aronson; Wendy K. Chung; Stacy W. Gray; Lucia A. Hindorff; Gail P. Jarvik; Sharon E. Plon; Elena M. Stoffel; Peter Tarczy-Hornoch; Eliezer M. Van Allen; Karen E. Weck; et al. (J. Am. Medical Informatics Assoc., 2015)

Developing an NLP Pipeline for Thyroid Ultrasound Reporting. - Rajesh Koralkar; Eric LaRose; Yiqiang Song; David F. Schneider; Peggy L. Peissig (AMIA, 2016)

Baseline Regularization for Computational Drug Repositioning with Longitudinal Observational Data. - Zhaobin Kuang; James A. Thomson; Michael Caldwell; Peggy L. Peissig; Ron M. Stewart; David Page (IJCAI, 2016)

OCR as a Service: An Experimental Evaluation of Google Docs OCR, Tesseract, ABBYY FineReader, and Transym. - Ahmad Pahlavan Tafti; Ahmadreza Baghaie; Mehdi Assefi; Hamid R. Arabnia; Zeyun Yu; Peggy L. Peissig (ISVC (1), 2016)

Computational Drug Repositioning Using Continuous Self-Controlled Case Series. - Zhaobin Kuang; James A. Thomson; Michael Caldwell; Peggy L. Peissig; Ron M. Stewart; David Page (KDD, 2016)

Discriminatory power of common genetic variants in personalized breast cancer diagnosis. - Yirong Wu; Craig K. Abbey; Jie Liu 006; Irene M. Ong; Peggy L. Peissig; Adedayo A. Onitilo; Jun Fan; Ming Yuan 001; Elizabeth S. Burnside (Image Perception, Observer Performance, and Technology Assessment, 2016)

Knowledge Driven Binning and PheWAS Analysis in Marshfield Personalized Medicine Research Project Using BioBin. - Anna Okula Basile; John R. Wallace; Peggy L. Peissig; Catherine A. McCarty; Murray H. Brilliant; Marylyn D. Ritchie (PSB, 2016)

Biofilter as a Functional Annotation Pipeline for Common and Rare Copy Number Burden. - Dokyoon Kim; Anastasia Lucas; Joseph Glessner; Shefali S. Verma; Yukiko Bradford; Ruowang Li; Alex T. Frase; Hakon Hakonarson; Peggy L. Peissig; Murray H. Brilliant; Marylyn D. Ritchie (PSB, 2016)

Practical considerations for implementing genomic information resources. - Casey L. Overby; John J. Connolly; Christopher G. Chute; Joshua C. Denny; Robert R. Freimuth; Andrea L. Hartzler; Ingrid A. Holm; Shannon F. Manzi; Jyotishman Pathak; Peggy L. Peissig; Maureen E. Smith; Marc S. Williams; et al. (Appl. Clin. Inform., 2016)

Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network. - Ruowang Li; Scott M. Dudek; Dokyoon Kim; Molly A. Hall; Yukiko Bradford; Peggy L. Peissig; Murray H. Brilliant; James G. Linneman; Catherine A. McCarty; Le Bao; Marylyn D. Ritchie (BioData Min., 2016)

A multi-institution evaluation of clinical profile anonymization. - Raymond Heatherly; Luke V. Rasmussen; Peggy L. Peissig; Jennifer A. Pacheco; Paul A. Harris; Joshua C. Denny; Bradley A. Malin (J. Am. Medical Informatics Assoc., 2016)

PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability. - Jacqueline Kirby; Peter Speltz; Luke V. Rasmussen; Melissa A. Basford; Omri Gottesman; Peggy L. Peissig; Jennifer A. Pacheco; Gerard Tromp; Jyotishman Pathak; David S. Carrell; Stephen B. Ellis; Todd Lingren; et al. (J. Am. Medical Informatics Assoc., 2016)

Structure-Leveraged Methods in Breast Cancer Risk Prediction. - Jun Fan; Yirong Wu; Ming Yuan 001; David Page; Jie Liu 006; Irene M. Ong; Peggy L. Peissig; Elizabeth S. Burnside (J. Mach. Learn. Res., 2016)

Relational Learning for Sustainable Health. - Sriraam Natarajan; Peggy L. Peissig; David Page (Computational Sustainability, 2016)

bigNN: An open-source big data toolkit focused on biomedical sentence classification. - Ahmad Pahlavan Tafti; Ehsun Behravesh; Mehdi Assefi; Eric LaRose; Jonathan C. Badger; John Mayer; AnHai Doan; David Page; Peggy L. Peissig (IEEE BigData, 2017)

SCCS for Detection of Differences in Brand and Generic Adverse Drug Events. - Jonathan C. Badger; Eric R. LaRose; Ross Kleiman; Richard L. Berg; James G. Linneman; Richard Hansen; David Page; Peggy L. Peissig (CRI, 2017)

Entity Matching Using Magellan: Matching Drug Reference Tables. - Eric R. LaRose; Jonathan C. Badger; Pradap Konda; AnHai Doan; Peggy L. Peissig (CRI, 2017)

Breast Cancer Risk Prediction Using Electronic Health Records. - Yirong Wu; Elizabeth S. Burnside; Jennifer Cox; Jun Fan; Ming Yuan 001; Jie Yin; Peggy L. Peissig; Alexander G. Cobian; David Page; Mark W. Craven (ICHI, 2017)

Pharmacovigilance via Baseline Regularization with Large-Scale Longitudinal Observational Data. - Zhaobin Kuang; Peggy L. Peissig; Vítor Santos Costa; Richard Maclin; David Page (KDD, 2017)

Machine Learning-as-a-Service and Its Application to Medical Informatics. - Ahmad Pahlavan Tafti; Eric LaRose; Jonathan C. Badger; Ross Kleiman; Peggy L. Peissig (MLDM, 2017)

Hawkes Process Modeling of Adverse Drug Reactions with Longitudinal Observational Data. - Yujia Bao; Zhaobin Kuang; Peggy L. Peissig; David Page; Rebecca Willett (MLHC, 2017)

Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals. - Pedro L. Teixeira; Wei-Qi Wei; Robert M. Cronin; Huan Mo; Jacob P. VanHouten; Robert J. Carroll; Eric LaRose; Lisa Bastarache; S. Trent Rosenbloom; Todd L. Edwards; Dan M. Roden; Thomas A. Lasko; et al. (J. Am. Medical Informatics Assoc., 2017)

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 006; Peggy L. Peissig; Adedayo A. Onitilo; Jennifer Cox; David Page; Elizabeth S. Burnside (AMIA, 2018)

Diagnostic Classification of Lung CT Images Using Deep 3D Multi-Scale Convolutional Neural Network. - Ahmad Pahlavan Tafti; Fereshteh S. Bashiri; Eric LaRose; Peggy L. Peissig (ICHI, 2018)

Temporal Poisson Square Root Graphical Models. - Sinong Geng; Zhaobin Kuang; Peggy L. Peissig; David Page (ICML, 2018)

Object Detection to Assist Visually Impaired People: A Deep Neural Network Adventure. - Fereshteh S. Bashiri; Eric LaRose; Jonathan C. Badger; Roshan M. D'Souza; Zeyun Yu; Peggy L. Peissig (ISVC, 2018)

Quantifying predictive capability of electronic health records for the most harmful breast cancer. - Yirong Wu; Jun Fan; Peggy L. Peissig; Richard L. Berg; Ahmad Pahlavan Tafti; Jie Yin; Ming Yuan 001; David Page; Jennifer Cox; Elizabeth S. Burnside (Image Perception, Observer Performance, and Technology Assessment, 2018)

A case study evaluating the portability of an executable computable phenotype algorithm across multiple institutions and electronic health record environments. - Jennifer A. Pacheco; Luke V. Rasmussen; Richard C. Kiefer; Thomas R. Campion Jr.; Peter Speltz; Robert J. Carroll; Sarah C. Stallings; Huan Mo; Monika Ahuja; Guoqian Jiang; Eric R. LaRose; Peggy L. Peissig; et al. (J. Am. Medical Informatics Assoc., 2018)

Lung Nodule Classification Using Combined Deep and Spectral 3D Shape Features. - Fereshteh S. Bashiri; Jonathan C. Badger; Roshan M. D'Souza; Zeyun Yu; Peggy L. Peissig (BHI, 2019)

An Application of Manifold Learning in Global Shape Descriptors. - Fereshteh S. Bashiri; Reihaneh Rostami; Peggy L. Peissig; Roshan M. D'Souza; Zeyun Yu (Algorithms, 2019)

High-Throughput Machine Learning from Electronic Health Records. - Ross S. Kleiman; Paul S. Bennett; Peggy L. Peissig; Richard L. Berg; Zhaobin Kuang; Scott J. Hebbring; Michael D. Caldwell; David Page (CoRR, 2019)

Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network. - Timothy M. Herr; Josh F. Peterson; Luke V. Rasmussen; Pedro J. Caraballo; Peggy L. Peissig; Justin B. Starren (J. Am. Medical Informatics Assoc., 2019)

Machine learning for phenotyping opioid overdose events. - Jonathan C. Badger; Eric LaRose; John Mayer; Fereshteh S. Bashiri; David Page; Peggy L. Peissig (J. Biomed. Informatics, 2019)

Facilitating phenotype transfer using a common data model. - George Hripcsak; Ning Shang; Peggy L. Peissig; Luke V. Rasmussen; Cong Liu 020; Barbara Benoit; Robert J. Carroll; David S. Carrell; Joshua C. Denny; Ozan Dikilitas; Vivian S. Gainer; Kayla Marie Howell; et al. (J. Biomed. Informatics, 2019)

Adverse drug reaction discovery from electronic health records with deep neural networks. - Wei Zhang 058; Zhaobin Kuang; Peggy L. Peissig; David Page (CHIL, 2020)

High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records. - Alexander K. Taylor 001; Ross Kleiman; Scott J. Hebbring; Peggy L. Peissig; David Page (CoRR, 2020)

Medical records-based chronic kidney disease phenotype for clinical care and "big data" observational and genetic studies. - Ning Shang; Atlas Khan; Fernanda Polubriaginof; Francesca Zanoni; Karla Mehl; David Fasel; Paul E. Drawz; Robert J. Carroll; Joshua C. Denny; Matthew A. Hathcock; Adelaide M. Arruda-Olson; Peggy L. Peissig; et al. (npj Digit. Medicine, 2021)

Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions. - Jingzhi Yu; Jennifer A. Pacheco; Anika S. Ghosh; Yuan Luo 001; Chunhua Weng; Ning Shang; Barbara Benoit; David S. Carrell; Robert J. Carroll; Ozan Dikilitas; Robert R. Freimuth; Vivian S. Gainer; et al. (BMC Medical Informatics Decis. Mak., 2022)

Temporal Inverse Probability Weighting for Causal Discovery in Controlled Before-After Studies: Discovering ADEs in Generics. - Aubrey Barnard; Peggy L. Peissig; David Page (CLeaR, 2025)