ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018
Clinical text annotation - what factors are associated with the cost of time?
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Semantic Similarity Search Approach to Extract Exemplars of Stigmatizing and Positive Language in Obstetric Clinical Notes: Exploratory Study.JMIR medical informatics · 2026Article
- A Sentence Classification-Based Medical Status Extraction Pipeline for Electronic Health Records: Institutional Case Study.JMIR medical informatics · 2026Article
- SDoH-GPT: using large language models to extract social determinants of health.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Enhancing hepatopathy clinical trial efficiency: a secure, large language model-powered pre-screening pipeline.BioData mining · 2025Article
- Enhancing Bidirectional Encoder Representations From Transformers (BERT) With Frame Semantics to Extract Clinically Relevant Information From German Mammography Reports: Algorithm Development and Validation.Journal of medical Internet research · 2025Article
- LC-YOLOmatch: a novel scene segmentation approach based on YOLO for laparoscopic cholecystectomy.Frontiers in artificial intelligence · 2025Article
- Lessons learned: Development of COVID-19 clinical staging models at a large urban research institution.Journal of clinical and translational science · 2023Article
- The h-ANN Model: Comprehensive Colonoscopy Concept Compilation Using Combined Contextual Embeddings.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022Article
- TAX-Corpus: Taxonomy based Annotations for Colonoscopy Evaluation.Biomedical engineering systems and technologies, international joint conference, BIOSTEC ... revised selected papers. BIOSTEC (Conference) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Building high-quality annotated clinical corpora is necessary for developing statistical Natural Language Processing (NLP) models to unlock information embedded in clinical text, but it is also time consuming and expensive. Consequently, it important to identify factors that may affect annotation time, such as syntactic complexity of the text- to-be-annotated and the vagaries of individual user behavior. However, limited work has been done to understand annotation of clinical text. In this study, we aimed to investigate how factors inherent to the text affect annotation time for a named entity recognition (NER) task. We recruited 9 users to annotate a clinical corpus and recorded annotation time for each sample. Then we defined a set of factors that we hypothesized might affect annotation time, and fitted them into a linear regression model to predict annotation time. The linear regression model achieved an R
Indexed as
Identifiers
30815201PMC6371268What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.