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Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data
Gregory P Finley
,
Serguei V.S. Pakhomov
, Reed McEwan
,
Genevieve B. Melton
Surgery
Pharmaceutical Care and Health Systems
Transplant and Cellular Therapy
Research output
:
Contribution to journal
›
Article
›
peer-review
28
Scopus citations
Overview
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Dive into the research topics of 'Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data'. Together they form a unique fingerprint.
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Keyphrases
Training Data
100%
Abbreviation Disambiguation
100%
Clinical Abbreviations
100%
Medical Records
33%
Clinical Text
33%
BioNLP
33%
Semi-supervised Method
33%
Supervised Machine Learning
33%
Long-form
33%
Semi-supervised Classification
33%
NLP System
33%
Supervised Classification Algorithm
33%
Realistic Use
33%
Specialized Corpus
33%
Natural Text
33%
Fully-supervised
33%
Computer Science
Training Data
100%
Disambiguation
100%
Medical Record
33%
Use Case
33%
Classification Algorithm
33%
Supervised Classification
33%
Machine Learning
33%
Learning System
33%