Sungrim Moon, Ph.D.
Affiliations: | 2012 | Health Informatics | University of Minnesota, Twin Cities, Minneapolis, MN |
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"Sungrim Moon"Parents
Sign in to add mentor| Serguei V. Pakhomov | grad student | 2012 | UMN | |
| (Automatic word sense disambiguation of acronyms and abbreviations in clinical texts.) | ||||
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Publications
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| Miller K, Moon S, Fu S, et al. (2024) Contextual Variation of Clinical Notes induced by EHR Migration. Amia ... Annual Symposium Proceedings. Amia Symposium. 2023: 1155-1164 |
| Fu S, Chen D, He H, et al. (2020) Clinical Concept Extraction: a Methodology Review. Journal of Biomedical Informatics. 103526 |
| Moon S, Liu S, Chen D, et al. (2019) Salience of Medical Concepts of Inside Clinical Texts and Outside Medical Records for Referred Cardiovascular Patients. Journal of Healthcare Informatics Research. 3: 200-219 |
| Moon S, Liu S, Scott CG, et al. (2019) Automated extraction of sudden cardiac death risk factors in hypertrophic cardiomyopathy patients by natural language processing. International Journal of Medical Informatics. 128: 32-38 |
| Wu S, Liu S, Sohn S, et al. (2018) Modeling Asynchronous Event Sequences with RNNs. Journal of Biomedical Informatics |
| Wi C, Lee S, Moon S, et al. (2018) Automated Chart Review for Identifying Factors Associated with Childhood Asthma by Utilizing Electronic Medical Records The Journal of Allergy and Clinical Immunology. 141 |
| Wang Y, Wang L, Rastegar-Mojarad M, et al. (2017) Clinical Information Extraction Applications: A Literature Review. Journal of Biomedical Informatics |
| Chen Y, Lask TA, Mei Q, et al. (2017) An active learning-enabled annotation system for clinical named entity recognition. Bmc Medical Informatics and Decision Making. 17: 82 |
| Juhn YJ, Wi C, Seol HY, et al. (2017) Application of Natural Language Processing algorithm for Predetermine Asthma Criteria to ascertainment of adult-onset asthma European Respiratory Journal. 50 |
| Moon S, McInnes B, Melton GB. (2015) Challenges and practical approaches with word sense disambiguation of acronyms and abbreviations in the clinical domain. Healthcare Informatics Research. 21: 35-42 |