Displaying results 1 - 8 of 9
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Pilot Evaluation of Syndrome-specific School Absenteeism Data for Public Health Surveillance
Content Type: Abstract
School absenteeism data could be used as an early indicator for disease outbreaks. The increase in absences, however, may be driven by non-sickness related factors. Reason for absence combined with syndrome-specific information… read more -
Automated Detection of GI Syndrome using Structured and Non-Structured Data from the VA EMR
Content Type: Abstract
Objective We performed a gold-standard manual chart review for gastro-intestinal syndrome to evaluate automated detection models based on both structured and non-structured data extracted from the VA … read more -
Free-Text Processing To Enhance Detection Of Acute Respiratory Infections
Content Type: Abstract
Objective We asked to what extent computerized processing of the full free-text clinical documentation could enhance syndrome detection compared to the sole use of structured data elements from a comprehensive… read more -
Identifying Contextual Features to Improve the Performance of an Influenza-Like Illness Text Classifier
Content Type: Abstract
To understand the types of false positive cases identified by an Influenza-like illness (ILI) text classifier by measuring the prevalence of ILI-related concepts that are negated, hypothetical, include explicit mention of temporality, experienced by… read more -
Computerized Text Analysis to Enhance Automated Pneumonia Detection
Content Type: Abstract
Information about disease severity could help with both detection and situational awareness during outbreaks of acute respiratory infections (ARI). In this work, we use data from the EMR to identify patients with pneumonia, a key landmark of ARI… read more -
Extracting Surveillance Data from Templated Sections of an Electronic Medical Note: Challenges and Opportunities
Content Type: Abstract
The main stay of recording patient data is the free text of electronic medical records (EMR). While stating the chief complaint and history of presenting illness in the patients ‘own words’, the rest of the electronic note is written by the provider… read more -
Clinical decision support at the time of an e-prescription can sustainably decrease unwarranted use of antibiotics for acute respiratory infections
Content Type: Abstract
Microorganisms resistant to antibiotics (ABX) increase the mortality, morbidity and costs of infections. In the absence of a drug development pipeline that can keep pace with the emerging resistancemechanisms, these organisms are expected… read more -
Using clinician mental models to guide annotation of medically unexplained symptoms and syndromes found in VA clinical documents
Content Type: Abstract
Medically unexplained syndromes (MUS) are conditions that are diagnosed on the basis of symptom constellations and are characterized by a lack of well-defined pathogenic pathways. The three most common MUS are chronic fatigue … read more