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To investigate the agreement among clinical experts in their judgments of monitoring data with respect to artifacts, and to examine the effect of reference standards that consist of individual and joint expert judgments on the performance of artifact filters.

To develop software infrastructure that will provide support for discovery, characterization, integrated access, and management of diverse and disparate collections of information sources, analysis methods, and applications in biomedical research.

We conducted a prospective observational study to (1) determine usage and construct validity of a method to gauge the cognitive impact of information derived from daily e-mail, and (2) describe self-reported impacts of research-based synopses (InfoPOEMs) delivered as e-mail. Ratings of InfoPOEMs using an Impact assessment scale provided (a) data on usage of the impact assessment method, (b) reports of impact by InfoPOEM and by doctor and (c) data for [...]

Monitoring vital signs and locations of certain classes of ambulatory patients can be useful in overcrowded emergency departments and at disaster scenes, both on-site and during transportation. To be useful, such monitoring needs to be portable and low cost, and have minimal adverse impact on emergency personnel, e.g., by not raising an excessive number of alarms. The SMART (Scalable Medical Alert Response Technology) system integrates wireless patient monitoring (ECG, SpO(2)) [...]

Explore the automated acquisition of knowledge in biomedical and clinical documents using text mining and statistical techniques to identify disease-drug associations.

This article describes our system entry for the 2006 I2B2 contest "Challenges in Natural Language Processing for Clinical Data" for the task of identifying the smoking status of patients. Our system makes the simplifying assumption that patient-level smoking status determination can be achieved by accurately classifying individual sentences from a patient's record. We created our system with reusable text analysis components built on the Unstructured Information Management Architecture and Weka [...]

TimeText is a temporal reasoning system designed to represent, extract, and reason about temporal information in clinical text.

The anonymization of medical records is of great importance in the human life sciences because a de-identified text can be made publicly available for non-hospital researchers as well, to facilitate research on human diseases. Here the authors have developed a de-identification model that can successfully remove personal health information (PHI) from discharge records to make them conform to the guidelines of the Health Information Portability and Accountability Act.

To determine the accuracy of self-reported information from patients and families for use in a disease surveillance system.

Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines.