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This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks.

To identify predictors of nurses' acceptance of bar coded medication administration (BCMA).

The conduct of clinical and translational research regularly involves the use of a variety of heterogeneous and large-scale data resources. Scalable methods for the integrative analysis of such resources, particularly when attempting to leverage computable domain knowledge in order to generate actionable hypotheses in a high-throughput manner, remain an open area of research. In this report, we describe both a generalizable design pattern for such integrative knowledge-anchored hypothesis discovery operations [...]

The demographic and practice-related characteristics of physicians who use social networking websites, portable devices to access the internet, email to communicate with patients, podcasts, widgets, RSS feeds, and blogging were investigated. Logistic regression was used to analyze a survey of US primary care physicians, pediatricians, obstetrician/gynecologists, and dermatologists (N=1750). Reported technology use during the last 6 months ranged from 80.6% using a portable device to access the internet to 12.9% [...]

To determine the frequency with which computerized alerts occur and the proportion triggered as a result of prescribers not utilizing e-prescribing system functions.

A system that translates narrative text in the medical domain into structured representation is in great demand. The system performs three sub-tasks: concept extraction, assertion classification, and relation identification.

Design and evaluation of the dietary intake monitoring application (DIMA) to assist varying-literacy patients receiving hemodialysis to adhere to their prescribed dietary regimen.

Postoperative nausea and vomiting (PONV) is a frequent complication in patients undergoing ambulatory surgery, with an incidence of 20%-65%. A predictive model can be utilized for decision support and feedback for practitioner practice improvement. The goal of this study was to develop a better model to predict the patient's risk for PONV by incorporating both non-modifiable patient characteristics and modifiable practitioner-specific anesthetic practices.

We describe a novel, crowdsourcing method for generating a knowledge base of problem-medication pairs that takes advantage of manually asserted links between medications and problems.

Clinical research is the foundation for advancing the practice of medicine. However, the lack of seamless integration between clinical research and patient care workflow impedes recruitment efficiency, escalates research costs, and hence threatens the entire clinical research enterprise. Increased use of electronic health records (EHRs) holds promise for facilitating this integration but must surmount regulatory obstacles. Among the unintended consequences of current research oversight are barriers to accessing patient information [...]