Severe sepsis and septic shock are conditions that affect millions of patients and have close to 50% mortality rate. Early identification of at-risk patients ...
Sep 11, 2018 · Early identification of at-risk patients significantly improves outcomes. Electronic surveillance tools have been developed to monitor ...
... To identify patients with infection in nursing notes we developed a supervised ML algorithm utilizing a bag-of-words [59] and linear kernel SVMs [ ...
Sep 11, 2018 · A method for automatic monitoring of nursing notes for signs and symptoms of infection and a Machine Learning model that achieved an F1-score ranging from 79 ...
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Sep 11, 2018 · Toward Automated Early Sepsis Alerting: Identifying Infection Patients from Nursing Notes. Emilia Apostolova. Language.ai. Chicago, IL, USA.
Severe sepsis and septic shock are conditions that affect millions of patients and have close to 50 patients significantly improves outcomes.
The electronic health record can be used to identify patients with sepsis, improve participant study recruitment, and extract data.
Dec 13, 2021 · Identify notes with suspected or presence of infection to develop a system for detecting infection signs and symptoms in free-text nursing notes ...
It was hoped this alert/warning system would clearly identify septic patients, lead to earlier interventions, prevent transfers to a higher level of care, and ...
identified with sepsis or septic shock and compared 30 patients prior to electronic alert initiation with 30 patients after initiation. The primary endpoint ...