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Relation extraction in biomedical text mining systems has largely focused on identifying clause-level relations, but increasing sophistication demands the recognition of relations at discourse level. A first step in identifying discourse relations involves the detection of discourse connectives: words or phrases used in text to express discourse relations. In this study supervised machine-learning approaches were developed and evaluated for automatically identifying discourse connectives in biomedical text.

To describe an analytical framework for quantifying the societal savings and financial consequences of a health information exchange (HIE), and to demonstrate its use in designing pricing policies for sustainable HIEs.

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 [...]

Drug-drug interactions (DDIs) are responsible for many serious adverse events; their detection is crucial for patient safety but is very challenging. Currently, the US Food and Drug Administration and pharmaceutical companies are showing great interest in the development of improved tools for identifying DDIs.

A method for the automatic resolution of coreference between medical concepts in clinical records.

The classification of complex or rare patterns in clinical and genomic data requires the availability of a large, labeled patient set. While methods that operate on large, centralized data sources have been extensively used, little attention has been paid to understanding whether models such as binary logistic regression (LR) can be developed in a distributed manner, allowing researchers to share models without necessarily sharing patient data.

To test the reliability, validity, acceptability, and practicality of short message service (SMS) messaging for collection of research data.

Narratives of electronic medical records contain information that can be useful for clinical practice and multi-purpose research. This information needs to be put into a structured form before it can be used by automated systems. Coreference resolution is a step in the transformation of narratives into a structured form.

The AMIA Public Health Informatics 2011 Conference brought together members of the public health and health informatics communities to revisit the national agenda developed at the AMIA Spring Congress in 2001, assess the progress that has been made in the past decade, and develop recommendations to further guide the field. Participants met in five discussion tracks: technical framework; research and evaluation; ethics; education, professional training, and workforce development; and sustainability [...]

Semantic similarity analysis facilitates automated semantic explanations of biological and clinical data annotated by biomedical ontologies. Gene ontology (GO) has become one of the most important biomedical ontologies with a set of controlled vocabularies, providing rich semantic annotations for genes and molecular phenotypes for diseases. Current methods for measuring GO semantic similarities are limited to considering only the ancestor terms while neglecting the descendants. One can find many GO term [...]