ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2014
Facilitating post-surgical complication detection through sublanguage analysis.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 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
4 citing papers in PubMed.
- Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.Journal of the American College of Surgeons · 2021Article
- Detection of Surgical Site Infection Utilizing Automated Feature Generation in Clinical Notes.Journal of healthcare informatics research · 2019Article
- Detection of clinically important colorectal surgical site infection using Bayesian network.The Journal of surgical research · 2017Article
- Predicate Oriented Pattern Analysis for Biomedical Knowledge Discovery.Intelligent information management · 2016Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Identification of postsurgical complications is the first step towards improving patient safety and health care quality as well as reducing heath care cost. Existing NLP-based approaches for retrieving postsurgical complications are based on search strategies. Here, we conduct a sublanguage analysis study using free text reports available for a cohort of patients with postsurgical complications identified manually to compare the keywords identified by subject matter experts with words/phrases automatically identified by sublanguage analysis. The results suggest that search-based approaches may miss some cases and the sublanguage analysis results can be used as a base to develop an information extraction system or support search-based NLP approaches by augmenting search queries.
Identifiers
25717405PMC4333707What 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.