Leonard W. D'Avolio

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8 This issue of JAMIA focuses on natural language processing (NLP) techniques for clinical-text information extraction. Several articles are offshoots of the yearly 'Informatics for Integrating Biology and the Bedside' (i2b2) (http://www.i2b2.org) NLP shared-task challenge, introduced by Uzuner et al (see page 552) 1 and co-sponsored by the Veteran's(More)
OBJECTIVE Despite at least 40 years of promising empirical performance, very few clinical natural language processing (NLP) or information extraction systems currently contribute to medical science or care. The authors address this gap by reducing the need for custom software and rules development with a graphical user interface-driven, highly generalizable(More)
BACKGROUND Timely information about disease severity can be central to the detection and management of outbreaks of acute respiratory infections (ARI), including influenza. We asked if two resources: 1) free text, and 2) structured data from an electronic medical record (EMR) could complement each other to identify patients with pneumonia, an ARI severity(More)
Surgical procedures can be viewed as a process composed of a sequence of steps performed on, by, or with the patient's anatomy. This sequence is typically the pattern followed by surgeons when generating surgical report narratives for documenting surgical procedures. This paper describes a methodology for semi-automatically deriving a model of conducted(More)
Reducing custom software development effort is an important goal in information retrieval (IR). This study evaluated a generalizable approach involving with no custom software or rules development. The study used documents "consistent with cancer" to evaluate system performance in the domains of colorectal (CRC), prostate (PC), and lung (LC) cancer. Using(More)
Open source natural language processing (NLP) frameworks have made it easier for NLP developers and researchers to develop more reusable and modular components and to capitalize on the work of others. With the Automated Retrieval Console (ARC) we attempt to build upon this foundation by streamlining the many processes surrounding the development,(More)
Information retrieval algorithms based on natural language processing (NLP) of the free text of medical records have been used to find documents of interest from databases. Homelessness is a high priority non-medical diagnosis that is noted in electronic medical records of Veterans in Veterans Affairs (VA) facilities. Using a human-reviewed reference(More)
The Clinical Outcomes Assessment Toolkit (COAT) was created through a collaboration between the University of California, Los Angeles and Brigham and Women's Hospital to address the challenge of gathering, formatting, and abstracting data for clinical outcomes and performance measurement research. COAT provides a framework for the development of information(More)
OBJECTIVES The Massachusetts Veterans Epidemiology Research and Information Center in collaboration with the Stanford Center for Innovative Study Design set out to test the feasibility of a new method of evidence generation. The first pilot of a point-of-care clinical trial (POCCT), adding randomization and other study processes to an electronic medical(More)