Kevin Lybarger
Orcid: 0000-0001-5798-2664
According to our database1,
Kevin Lybarger
authored at least 30 papers
between 2017 and 2024.
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Bibliography
2024
Extracting Social Determinants of Health from Pediatric Patient Notes Using Large Language Models: Novel Corpus and Methods.
CoRR, 2024
A Novel Corpus of Annotated Medical Imaging Reports and Information Extraction Results Using BERT-based Language Models.
CoRR, 2024
Health Text Simplification: An Annotated Corpus for Digestive Cancer Education and Novel Strategies for Reinforcement Learning.
CoRR, 2024
2023
J. Am. Medical Informatics Assoc., July, 2023
Advancements in extracting social determinants of health information from narrative text.
J. Am. Medical Informatics Assoc., July, 2023
Leveraging natural language processing to augment structured social determinants of health data in the electronic health record.
J. Am. Medical Informatics Assoc., July, 2023
Integrating patient voices into the extraction of social determinants of health from clinical notes: ethical considerations and recommendations.
J. Am. Medical Informatics Assoc., July, 2023
Extracting medication changes in clinical narratives using pre-trained language models.
J. Biomed. Informatics, March, 2023
Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model.
J. Digit. Imaging, February, 2023
MasonNLP+ at SemEval-2023 Task 8: Extracting Medical Questions, Experiences and Claims from Social Media using Knowledge-Augmented Pre-trained Language Models.
Proceedings of the The 17th International Workshop on Semantic Evaluation, 2023
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), 2023
Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023
2022
Leveraging Natural Language Processing to Augment Structured Social Determinants of Health Data in the Electronic Health Record.
CoRR, 2022
Generalizing through Forgetting - Domain Generalization for Symptom Event Extraction in Clinical Notes.
CoRR, 2022
Improving Classification of Infrequent Cognitive Distortions: Domain-Specific Model vs. Data Augmentation.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Student Research Workshop, 2022
A Corpus of Radiology Reports From Multiple Imaging Modalities With Fine-grained Event-based Annotations.
Proceedings of the AMIA 2022, 2022
2021
Annotating social determinants of health using active learning, and characterizing determinants using neural event extraction.
J. Biomed. Informatics, 2021
Extracting COVID-19 diagnoses and symptoms from clinical text: A new annotated corpus and neural event extraction framework.
J. Biomed. Informatics, 2021
Event-based clinical findings extraction from radiology reports with pre-trained language model.
CoRR, 2021
Extracting Radiological Findings With Normalized Anatomical Information Using a Span-Based BERT Relation Extraction Model.
CoRR, 2021
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Identifying ARDS using the Hierarchical Attention Network with Sentence Objectives Framework.
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
Proceedings of the AMIA 2021, American Medical Informatics Association Annual Symposium, San Diego, CA, USA, October 30, 2021, 2021
2020
Proceedings of the AMIA 2020, 2020
2019
Proceedings of the AMIA 2019, 2019
2018
Using voice to create hospital progress notes: Description of a mobile application and supporting system integrated with a commercial electronic health record.
J. Biomed. Informatics, 2018
Appl. Clin. Inform., 2018
Using Neural Multi-task Learning to Extract Substance Abuse Information from Clinical Notes.
Proceedings of the AMIA 2018, 2018
2017
Improving Electronic Inpatient Progress Notes Using Voice: Results from the VGEENS Project.
Proceedings of the AMIA 2017, 2017
Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition.
Proceedings of the AMIA 2017, 2017