Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Reed McEwan"'
Autor:
Benjamin C. Knoll, Reed McEwan, Raymond Finzel, Greg Silverman, Rui Zhang, Serguei V.S. Pakhomov, Genevieve B. Melton
Publikováno v:
2022 IEEE 10th International Conference on Healthcare Informatics (ICHI).
Autor:
Raymond L. Finzel, Greg M. Silverman, V S Pakhomov Serguei, Reed McEwan, Michael Kotlyar, Shreya Datar, Genevieve B. Melton, Elizabeth A. Lindemann
Publikováno v:
ICHI
The impact of social determinants on individual health has increasingly been recognized. In this study, we aimed to understand the representation of stressful life events occurring in clinical reports generated outside of mental health specialties. W
Autor:
John W. Lyng, Greg M. Silverman, Christopher J. Tignanelli, Elizabeth A. Lindemann, Gregory J. Beilman, Alexander L. Trembley, Benjamin C. Knoll, Raymond L. Finzel, Genevieve B. Melton, Serguei V. S. Pakhomov, Reed McEwan, Jon C. Gipson
Publikováno v:
J Trauma Acute Care Surg
Background Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize
Autor:
Rui Zhang, Yadan Fan, Wendi Zhao, Reed McEwan, Serguei V. S. Pakhomov, Elizabeth A. Lindemann
Publikováno v:
JAMIA open
Objective The objective of this study is to demonstrate the feasibility of applying word embeddings to expand the terminology of dietary supplements (DS) using over 26 million clinical notes. Methods Word embedding models (ie, word2vec and GloVe) tra
Autor:
Greg M, Silverman, Elizabeth A, Lindemann, Geetanjali, Rajamani, Raymond L, Finzel, Reed, McEwan, Benjamin C, Knoll, Serguei, Pakhomov, Genevieve B, Melton, Christopher J, Tignanelli
Publikováno v:
Studies in health technology and informatics
Natural language processing (NLP) methods would improve outcomes in the area of prehospital Emergency Medical Services (EMS) data collection and abstraction. This study evaluated off-the-shelf solutions for automating labelling of clinically relevant
Autor:
Gretchen, Hultman, Reed, McEwan, Serguei, Pakhomov, Elizabeth, Lindemann, Steven, Skube, Genevieve B, Melton
Publikováno v:
AMIA Summits on Translational Science Proceedings
Natural Language Processing – Patient Information Extraction for Researchers (NLP-PIER) was developed for clinical researchers for self-service Natural Language Processing (NLP) queries with clinical notes. This study was to conduct a user-centered
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium. 2016
Abbreviation disambiguation in clinical texts is a problem handled well by fully supervised machine learning methods. Acquiring training data, however, is expensive and would be impractical for large numbers of abbreviations in specialized corpora. A
Publikováno v:
Geological Society of America Abstracts with Programs.
Publikováno v:
Past Global Change Magazine. 26:74-75
Autor:
Reed, McEwan, Genevieve B, Melton, Benjamin C, Knoll, Yan, Wang, Gretchen, Hultman, Justin L, Dale, Tim, Meyer, Serguei V, Pakhomov
Publikováno v:
AMIA Summits on Translational Science Proceedings
Many design considerations must be addressed in order to provide researchers with full text and semantic search of unstructured healthcare data such as clinical notes and reports. Institutions looking at providing this functionality must also address