Displaying results 9 - 15 of 15
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Using the Electronic Medical Record to Reduce both the Delay and the Workload Required to Detect and Influenza Epidemic
Content Type: Abstract
Measures aimed at controlling epidemics of infectious diseases critically benefit from early outbreak recognition. Through a manual electronic medical record (EMR) review of 5,127 outpatient encounters at the Veterans… 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 -
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 -
Reducing the Delay in Detecting an Influenza Epidemic with More Sensitive Case Detection Algorithms
Content Type: Abstract
Measures aimed at controlling epidemics of infectious diseases critically benefit from early outbreak recognition [1]. SSS seek early detection by focusing on pre-diagnostic symptoms that by themselves may not alarm clinicians. We have previously… read more -
Extending an Uncertainty Taxonomy for Suspected Pneumonia Case Review
Content Type: Abstract
Natural language processing algorithms that accurately screen clinical documents for suspected pneumonia must extract and reason about whether these mentions provide evidence that supports, refutes, or represents uncertainty. Our efforts extend… read more -
Classifying Supporting, Refuting, or Uncertain Evidence for Pneumonia Case Review
Content Type: Abstract
Characterizing mentions found in clinical texts that support, refute, or represent uncertainty for suspected pneumonia is one area where automated Natural Language Processing (NLP) screening algorithms could be improved. Mentions of uncertainty and… 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