Gordon R. Bernard

According to our database, Gordon R. Bernard authored at least 21 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

Large Language Model as Unsupervised Health Information Retriever.

Keyuan Jiang, Mohammed M. Mujtaba, Gordon R. Bernard

Proceedings of the Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023, Gothenburg, Sweden, 22, 2023

Answering List-Type Questions in Health Domain with Pretrained Large Language Model: A Case for COVID-19 Symptoms.

Keyuan Jiang, Mohammed M. Mujtaba, Gordon R. Bernard

Proceedings of the MEDINFO 2023 - The Future Is Accessible, 2023

Detection of Day-Based Health Evidence with Pretrained Large Language Models: A Case of COVID-19 Symptoms in Social Media Posts.

Keyuan Jiang, Valli Devendra, Soniya Chavan, Gordon R. Bernard

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022

Computer clinical decision support that automates personalized clinical care: a challenging but needed healthcare delivery strategy.

Alan H. Morris, Christopher Horvat, Brian Stagg, David W. Grainger, Michael Lanspa, James Orme, Terry P. Clemmer, Lindell K. Weaver, Frank Thomas, Colin K. Grissom, Ellie Hirshberg, Thomas D. East, Carrie Jane Wallace, Michael P. Young, Dean F. Sittig, Mary Suchyta, James E. Pearl, Antinio Pesenti, Michela Bombino, Eduardo Beck, Katherine A. Sward, Charlene R. Weir, Shobha Phansalkar, Gordon R. Bernard, B. Taylor Thompson, Roy Brower, Jonathon D. Truwit, Jay S. Steingrub, R. Duncan Hite, Douglas F. Willson, Jerry J. Zimmerman, Vinay Nadkarni, Adrienne G. Randolph, Martha A. Q. Curley, Christopher J. L. Newth, Jacques Lacroix, Michael S. D. Agus, Kang Hoe Lee, Bennett P. deBoisblanc, Frederick Alan Moore, R. Scott Evans, Dean K. Sorenson, Anthony Wong, Michael V. Boland, Willard H. Dere, Alan S. Crandall, Julio C. Facelli, Stanley M. Huff, Peter J. Haug, Ulrike Pielmeier, Stephen Edward Rees, Dan S. Karbing, Steen Andreassen, Eddy Fan, Roberta M. Goldring, Kenneth I Berger, Beno W. Oppenheimer, Eugene Wesley Ely, Brian W. Pickering, David A. Schoenfeld, Irena Tocino, Russell S. Gonnering, Peter J. Pronovost, Lucy A. Savitz, Didier Dreyfuss, Arthur S. Slutsky, James D. Crapo, Michael R. Pinsky, Brent James, Donald M. Berwick

J. Am. Medical Informatics Assoc., 2022

Few-Shot Learning for Identification of COVID-19 Symptoms Using Generative Pre-trained Transformer Language Models.

Keyuan Jiang, Minghao Zhu, Gordon R. Bernard

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Discovery of COVID-19 Symptomatic Experience Reported by Twitter Users.

Keyuan Jiang, Minghao Zhu, Gordon R. Bernard

Proceedings of the Challenges of Trustable AI and Added-Value on Health, 2022

2021

Enabling a learning healthcare system with automated computer protocols that produce replicable and personalized clinician actions.

Alan H. Morris, Brian Stagg, Michael Lanspa, James Orme, Terry P. Clemmer, Lindell K. Weaver, Frank Thomas, Colin K. Grissom, Ellie Hirshberg, Thomas D. East, Carrie Jane Wallace, Michael P. Young, Dean F. Sittig, Antonio Pesenti, Michela Bombino, Eduardo Beck, Katherine A. Sward, Charlene R. Weir, Shobha S. Phansalkar, Gordon R. Bernard, B. Taylor Thompson, Roy Brower, Jonathon D. Truwit, Jay S. Steingrub, R. Duncan Hite, Douglas F. Willson, Jerry J. Zimmerman, Vinay M. Nadkarni, Adrienne Randolph, Martha A. Q. Curley, Christopher J. L. Newth, Jacques Lacroix, Michael S. D. Agus, Kang H. Lee, Bennett P. deBoisblanc, R. Scott Evans, Dean K. Sorenson, Anthony Wong, Michael V. Boland, David W. Grainger, Willard H. Dere, Alan S. Crandall, Julio C. Facelli, Stanley M. Huff, Peter J. Haug, Ulrike Pielmeier, Stephen Edward Rees, Dan S. Karbing, Steen Andreassen, Eddy Fan, Roberta M. Goldring, Kenneth I. Berger, Beno W. Oppenheimer, Eugene Wesley Ely, Ognjen Gajic, Brian W. Pickering, David A. Schoenfeld, Irena Tocino, Russell S. Gonnering, Peter J. Pronovost, Lucy A. Savitz, Didier Dreyfuss, Arthur S. Slutsky, James D. Crapo, Derek C. Angus, Michael R. Pinsky, Brent James, Donald M. Berwick

J. Am. Medical Informatics Assoc., 2021

Mining Medication-Effect Relations from Twitter Data Using Pre-trained Transformer Language Model.

Keyuan Jiang, Dingkai Zhang, Gordon R. Bernard

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

Extraction of Medication-Effect Relations in Twitter Data with Neural Embedding and Recurrent Neural Network.

Keyuan Jiang, Dingkai Zhang, Gordon R. Bernard

Proceedings of the MEDINFO 2021: One World, One Health - Global Partnership for Digital Innovation, 2021

2020

Assessment of Word Embedding Techniques for Identification of Personal Experience Tweets Pertaining to Medication Uses.

Keyuan Jiang, Shichao Feng, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the Precision Health and Medicine - A Digital Revolution in Healthcare, 2020

Mining Potential Effects of HUMIRA in Twitter Posts Through Relational Similarity.

Keyuan Jiang, Shichao Feng, Liyuan Huang, Tingyu Chen, Gordon R. Bernard

Proceedings of the Digital Personalized Health and Medicine - Proceedings of MIE 2020, Medical Informatics Europe, Geneva, Switzerland, April 28, 2020

Mining Potentially Unreported Effects from Twitter Posts through Relational Similarity: A Case for Opioids.

Keyuan Jiang, Liyuan Huang, Tingyu Chen, Gelareh Karbaschi, Dingkai Zhang, Gordon R. Bernard

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

2019

Semantic Similarity of Side Effect and Indication Relations of Drugs Inferred from Neural Embedding.

Keyuan Jiang, Tingyu Chen, Liyuan Huang, Gelareh Karbaschi, Gordon R. Bernard

Proceedings of the 4th International Workshop on Semantics-Powered Data Mining and Analytics co-located with the 18th International Semantic Web Conference (ISWC 2019), 2019

Prediction of Personal Experience Tweets of Medication Use via Contextual Word Representations.

Keyuan Jiang, Tingyu Chen, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

An Explainable Approach of Inferring Potential Medication Effects from Social Media Data.

Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ravish Gupta, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems, 2019

2018

Identifying tweets of personal health experience through word embedding and LSTM neural network.

Keyuan Jiang, Shichao Feng, Qunhao Song, Ricardo A. Calix, Matrika Gupta, Gordon R. Bernard

BMC Bioinform., 2018

A Data-Driven Method of Discovering Misspellings of Medication Names on Twitter.

Keyuan Jiang, Tingyu Chen, Liyuan Huang, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the Building Continents of Knowledge in Oceans of Data: The Future of Co-Created eHealth, 2018

Identifying Consumer Health Terms of Side Effects in Twitter Posts.

Keyuan Jiang, Tingyu Chen, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the Data, 2018

2017

Predicting Major Adverse Kidney Events among Critically Ill Adults Using the Electronic Health Record.

Andrew C. McKown, Li Wang, Jonathan P. Wanderer, Jesse M. Ehrenfeld, Todd W. Rice, Gordon R. Bernard, Matthew W. Semler

J. Medical Syst., 2017

Identifying personal health experience tweets with deep neural networks.

Keyuan Jiang, Ravish Gupta, Matrika Gupta, Ricardo A. Calix, Gordon R. Bernard

Proceedings of the 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2017

2011

StarBRITE: The Vanderbilt University Biomedical Research Integration, Translation and Education portal.

Paul A. Harris, Jonathan A. Swafford, Terri L. Edwards, Minhua Zhang, Shraddha S. Nigavekar, Tonya R. Yarbrough, Lynda D. Lane, Tara Helmer, Laurie A. Lebo, Gail Mayo, Daniel R. Masys, Gordon R. Bernard, Jill M. Pulley

J. Biomed. Informatics, 2011