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The relationship between diseases and their causative genes can be complex, especially in the case of polygenic diseases. Further exacerbating the challenges in their study is that many genes may be causally related to multiple diseases. This study explored the relationship between diseases through the adaptation of an approach pioneered in the context of information retrieval: vector space models.

Adverse drug events (ADEs) are common and account for 770 000 injuries and deaths each year and drug interactions account for as much as 30% of these ADEs. Spontaneous reporting systems routinely collect ADEs from patients on complex combinations of medications and provide an opportunity to discover unexpected drug interactions. Unfortunately, current algorithms for such "signal detection" are limited by underreporting of interactions that are not expected. We present a novel [...]

To understand the nature of emerging electronic documentation practices, disconnects between documentation workflows and computing systems designed to support them, and ways to improve the design of electronic documentation systems.

The utility of healthcare utilization data from US emergency departments (EDs) for rapid monitoring of changes in influenza-like illness (ILI) activity was highlighted during the recent influenza A (H1N1) pandemic. Monitoring has tended to rely on detection algorithms, such as the Early Aberration Reporting System (EARS), which are limited in their ability to detect subtle changes and identify disease trends.

This paper explored pharmacy staff perceptions of the strengths and weaknesses of electronic prescribing (e-prescribing) design in retail pharmacies using the sociotechnical systems framework. This study examined how adoption of e-prescribing technology is affecting clinical practice and patient care.

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

The World Health Organization (WHO) actively promotes eHealth, which includes electronic health information systems, as means to generate better data on tuberculosis and on interventions to control tuberculosis. However, introducing electronic data management needs long-term investment in both staff and infrastructure and has profound social and organizational impacts. It is easy to make costly mistakes and to lose potential benefit due to poor organizational, technical, or financial planning and unrealistic [...]

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

The AMIA biomedical informatics (BMI) core competencies have been designed to support and guide graduate education in BMI, the core scientific discipline underlying the breadth of the field's research, practice, and education. The core definition of BMI adopted by AMIA specifies that BMI is 'the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving and decision making, motivated by [...]

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