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Evaluating the Applicability of Existing Lexicon-Based Sentiment Analysis Techniques on Family Medicine Resident Feedback Field Notes: Retrospective Cohort Study

Evaluating the Applicability of Existing Lexicon-Based Sentiment Analysis Techniques on Family Medicine Resident Feedback Field Notes: Retrospective Cohort Study

Future studies can focus on constructing a lexicon that accurately represents the vocabulary used in a medical education clinical setting, with a goal for 90% accuracy, which is the average target for domain-specific lexicons [18]. This may be achieved by taking a sample of existing field notes and having subject experts label pertinent words based on a new discrete sentiment scale.

Kevin Jia Qi Lu, Christopher Meaney, Elaine Guo, Fok-Han Leung

JMIR Med Educ 2023;9:e41953

Detecting Novel and Emerging Drug Terms Using Natural Language Processing: A Social Media Corpus Study

Detecting Novel and Emerging Drug Terms Using Natural Language Processing: A Social Media Corpus Study

Further complicating the matter, linguistic innovation is often magnified with the discussion of taboo substances and behaviors, which may cause drug-related vocabulary to emerge and recede more quickly than vocabulary in other domains [1].

Sean S Simpson, Nikki Adams, Claudia M Brugman, Thomas J Conners

JMIR Public Health Surveill 2018;4(1):e2

Text Simplification Using Consumer Health Vocabulary to Generate Patient-Centered Radiology Reporting: Translation and Evaluation

Text Simplification Using Consumer Health Vocabulary to Generate Patient-Centered Radiology Reporting: Translation and Evaluation

The UMLS Metathesaurus also includes the open-access, collaborative consumer health vocabulary (CHV) [20] developed by the Biomedical Informatics Department at the University of Utah as an open-source set of biomedical terms that are suitable for laypersons. Research that uses the term consumer health vocabulary started in 2003 [21], with the purpose of helping the lay public to understand health information [20].

Basel Abdulaziz Qenam, Tae Youn Kim, Mark J Carroll, Michael Hogarth

J Med Internet Res 2017;19(12):e417