PS1-21: Evaluation of Commercial Workflow Engine for Modeling Clinical Processes in Quality Improvement and Decision Support

par Huser, Vojtech, Peissig, Peggy L, Christensen, Carl A, Starren, Justin B
Publié 2010

Development of an optical character recognition pipeline for handwritten form fields from an electronic health record

par Rasmussen, Luke V, Peissig, Peggy L, McCarty, Catherine A, Starren, Justin
Publié 2011

Statistical Relational Learning to Predict Primary Myocardial Infarction from Electronic Health Records

par Weiss, Jeremy C, Page, David, Peissig, Peggy L, Natarajan, Sriraam, McCarty, Catherine
Publié 2012

Machine Learning Assisted Discovery of Novel Predictive Lab Tests Using Electronic Health Record Data

par Kleiman, Ross, Kuusisto, Finn, Ross, Ian, Peissig, Peggy L., Stewart, Ron, Page, C. David, Weiss, Jeremy
Publié dans AMIA Jt Summits Transl Sci Proc (2019)

Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network

par Herr, Timothy M, Peterson, Josh F, Rasmussen, Luke V, Caraballo, Pedro J, Peissig, Peggy L, Starren, Justin B
Publié dans J Am Med Inform Assoc (2018)

Practical challenges in integrating genomic data into the electronic health record

par Kho, Abel N., Rasmussen, Luke V., Connolly, John J., Peissig, Peggy L., Starren, Justin, Hakonarson, Hakon, Hayes, M. Geoffrey
Publié 2013

Relational Machine Learning for Electronic Health Record-Driven Phenotyping

par Peissig, Peggy L., Costa, Vitor Santos, Caldwell, Michael D., Rottscheit, Carla, Berg, Richard L., Mendonca, Eneida A., Page, David
Publié dans J Biomed Inform (2014)

A multi-institution evaluation of clinical profile anonymization

par Heatherly, Raymond, Rasmussen, Luke V, Peissig, Peggy L, Pacheco, Jennifer A, Harris, Paul, Denny, Joshua C, Malin, Bradley A
Publié dans J Am Med Inform Assoc (2016)

Using Machine Learning Algorithms to Predict Risk for Development of Calciphylaxis in Patients with Chronic Kidney Disease

par Kleiman, Ross S., LaRose, Eric R., Badger, Jonathan C., Page, David, Caldwell, Michael D., Clay, James A., Peissig, Peggy L.
Publié dans AMIA Jt Summits Transl Sci Proc (2018)

Cataract research using electronic health records

par Waudby, Carol J, Berg, Richard L, Linneman, James G, Rasmussen, Luke V, Peissig, Peggy L, Chen, Lin, McCarty, Catherine A
Publié 2011

Methodological considerations for comparison of brand versus generic versus authorized generic adverse event reports in the U.S. Food and Drug Administration Adverse Event Reportin...

par Rahman, Md. Motiur, Alatawi, Yasser, Cheng, Ning, Qian, Jingjing, Peissig, Peggy L., Berg, Richard L., Page, David C., Hansen, Richard A.
Publié dans Clin Drug Investig (2017)

Mixed approach retrospective analyses of suicide and suicidal ideation for brand compared with generic central nervous system drugs

par Cheng, Ning, Rahman, Md. Motiur, Alatawi, Yasser, Qian, Jingjing, Peissig, Peggy L., Berg, Richard L., Page, C. David, Hansen, Richard A.
Publié dans Drug Saf (2018)

Brand vs. generic adverse event reporting patterns: an authorized generic-controlled evaluation of cardiovascular medications

par Alatawi, Yasser, Rahman, Md. Motiur, Cheng, Ning, Qian, Jingjing, Peissig, Peggy L., Berg, Richard L., Page, C. David, Hansen, Richard A.
Publié dans J Clin Pharm Ther (2017)

An Evaluation of the NQF Quality Data Model for Representing Electronic Health Record Driven Phenotyping Algorithms

par Thompson, William K., Rasmussen, Luke V., Pacheco, Jennifer A., Peissig, Peggy L., Denny, Joshua C., Kho, Abel N., Miller, Aaron, Pathak, Jyotishman
Publié 2012

Comparison of Brand versus Generic Antiepileptic Drug Adverse Event Reporting Rates in the U.S. Food and Drug Administration Adverse Event Reporting System (FAERS)

par Rahman, Md. Motiur, Alatawi, Yasser, Cheng, Ning, Qian, Jingjing, Plotkina, Annya V., Peissig, Peggy L., Berg, Richard L., Page, David, Hansen, Richard A.
Publié dans Epilepsy Res (2017)

Comparison of outcomes following a switch from a brand to an authorized vs. independent generic drug

par Hansen, Richard A., Qian, Jingjing, Berg, Richard L., Linneman, James G., Seoane-Vazquez, Enrique, Dutcher, Sarah, Raofi, Saeid, Page, C. David, Peissig, Peggy L.
Publié dans Clin Pharmacol Ther (2017)

Design Patterns for the Development of Electronic Health Record-Driven Phenotype Extraction Algorithms

par Rasmussen, Luke V., Thompson, Will K., Pacheco, Jennifer A., Kho, Abel N., Carrell, David S., Pathak, Jyotishman, Peissig, Peggy L., Tromp, Gerard, Denny, Joshua C., Starren, Justin B.
Publié 2014

Identification of genetic interaction networks via an evolutionary algorithm evolved Bayesian network

par Li, Ruowang, Dudek, Scott M., Kim, Dokyoon, Hall, Molly A., Bradford, Yuki, Peissig, Peggy L., Brilliant, Murray H., Linneman, James G., McCarty, Catherine A., Bao, Le, Ritchie, Marylyn D.
Publié dans BioData Min (2016)

Knowledge-Driven Multi-Locus Analysis Reveals Gene-Gene Interactions Influencing HDL Cholesterol Level in Two Independent EMR-Linked Biobanks

par Turner, Stephen D., Berg, Richard L., Linneman, James G., Peissig, Peggy L., Crawford, Dana C., Denny, Joshua C., Roden, Dan M., McCarty, Catherine A., Ritchie, Marylyn D., Wilke, Russell A.
Publié 2011

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

par Peissig, Peggy L, Rasmussen, Luke V, Berg, Richard L, Linneman, James G, McCarty, Catherine A, Waudby, Carol, Chen, Lin, Denny, Joshua C, Wilke, Russell A, Pathak, Jyotishman, Carrell, David, Kho, Abel N, Starren, Justin B
Publié 2012