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References from Automating chart review for identification of infected patients using natural language processing. Local targets link to admitted publications; unresolved targets remain external evidence.
The third international consensus definitions for sepsis and septic shock (sepsis-3)
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Detecting sepsis: are two opinions better than one?
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Identifying patients with sepsis on the hospital wards
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The systemic inflammatory response syndrome (SIRS) to identify infected patients in the emergency room
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The SIRS criteria have better performance for predicting infection than qSOFA scores in the emergency department
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Determining the electronic signature of infection in electronic health record data
10.1097/ccm.0000000000004968 · 2021 · External reference
Sepsis prediction, early detection, and identification using clinical text for machine learning: a systematic review
10.1093/jamia/ocab236 · 2022 · External reference
Natural language processing of clinical notes for improved early prediction of septic shock in the ICU
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Contextual embeddings from clinical notes improves prediction of sepsis
2020 · External reference
Development and evaluation of a machine learning model for the early identification of patients at risk for sepsis
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Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare
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Creating an automated trigger for sepsis clinical decision support at emergency department triage using machine learning
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Early identification of suspected serious infection among patients afebrile at initial presentation using neural network models and natural language processing: a development and external validation study in the emergency department
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Automated medical chart review for breast cancer outcomes research: a novel natural language processing extraction system
10.1186/s12874-022-01583-z · 2022 · External reference
Automated chart review for asthma cohort identification using natural language processing: an exploratory study
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Using natural language processing to improve efficiency of manual chart abstraction in research: the case of breast cancer recurrence
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Cerebrovascular disease case identification in inpatient electronic medical record data using natural language processing
10.1186/s40708-023-00203-w · 2023 · External reference
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A tutorial on calibration measurements and calibration models for clinical prediction models
10.1093/jamia/ocz228 · 2020 · External reference
Assessment of clinical criteria for sepsis: for the third international consensus definitions for sepsis and septic shock (sepsis-3)
10.1001/jama.2016.0288 · 2016 · External reference
Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014
10.1001/jama.2017.13836 · 2017 · External reference
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Building predictive models in R using the caret package
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Unresolved reference
External reference
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10.1093/bioinformatics/btw570 · 2017 · External reference
Identifying infected patients using semi-supervised and transfer learning
10.1093/jamia/ocac109 · 2022 · External reference
Sepsis incidence and outcome: Contrasting the intensive care unit with the hospital ward
10.1097/01.ccm.0000260960.94300.de · 2007 · External reference
The epidemiology of acute organ system dysfunction from severe sepsis outside of the intensive care unit
10.1002/jhm.2012 · 2013 · External reference
Trends and opportunities in computable clinical phenotyping: a scoping review
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