Bayesian information fusion networks for biosurveillance applications.

This study introduces new information fusion algorithms to enhance disease surveillance systems with Bayesian decision support capabilities. A detection system was built and tested using chief complaints from emergency department visits, International Classification of Diseases Revision 9 (ICD-9) codes from records of outpatient visits to civilian and military facilities, and influenza surveillance data from health departments in the National Capital Region (NCR). Data anomalies were identified and distribution of time offsets between events in the multiple data streams were established.

Electronic medical record (EMR) utilization for public health surveillance.

Introduction: Public health surveillance systems need to be refined. We intend to use a generic approach for early identification of patients with severe influenza-like illness (ILI) by calculating a score that estimates a patients disease-severity. Accordingly, we built the Intelligent Severity Score Estimation Model (ISSEM), structured so that the inference process would reflect experts decision-making logic.

Bridging radiology and public health: the emerging field of radiologic public health informatics.

Radiology and public health have an emerging opportunity to collaborate, in which radiology's vast supply of imaging data can be integrated into public health information systems for epidemiologic assessments and responses to population health problems. Fueling the linkage of radiology and public health include (i) the transition from analog film to digital formats, enabling flexible use of radiologic data; (ii) radiology's role in imaging across nearly all medical and surgical subspecialties, which establishes a foundation for a consolidated and uniform database of images and reports for public health use; and (iii) the use of radiologic data to characterize disease patterns in a population occupying a geographic area at one time and to characterize disease progression over time via follow-up examinations. The backbone for this integration is through informatics projects such as Systematized Nomenclature of Medicine Clinical Terms and RadLex constructing terminology libraries and ontologies, as well as algorithms integrating data from the electronic health record and Digital Imaging and Communications in Medicine Structured Reporting.