Search AMIA.org

OBJECTIVE Automated and disease-specific classification of textual clinical discharge summaries is of great importance in human life science, as it helps physicians to make medical studies by providing statistically relevant data for analysis. This can be further facilitated if, at the labeling of discharge summaries, semantic labels are also extracted from text, such as whether a given disease is present, absent, questionable in a patient, or is unmentioned in the [...]

OBJECTIVE The authors present a system developed for the Challenge in Natural Language Processing for Clinical Data-the i2b2 obesity challenge, whose aim was to automatically identify the status of obesity and 15 related co-morbidities in patients using their clinical discharge summaries. The challenge consisted of two tasks, textual and intuitive. The textual task was to identify explicit references to the diseases, whereas the intuitive task focused on the prediction of [...]

Health care information technology can be a means to improve quality and efficiency in the primary care setting. However, merely applying technology without addressing how it fits into provider workflow and existing systems is unlikely to achieve improvement goals. Improving quality of primary care, such as cancer screening rates, requires addressing barriers at system, provider, and patient levels. The authors report the development, implementation, and preliminary use of a new [...]

Biomedical named entity recognition (BNER) is a critical component in automated systems that mine biomedical knowledge in free text. Among different types of entities in the domain, gene/protein would be the most studied one for BNER. Our goal is to develop a gene/protein name recognition system BioTagger-GM that exploits rich information in terminology sources using powerful machine learning frameworks and system combination.

This study sought to investigate user interactions with an electronic health records (EHR) system by uncovering hidden navigational patterns in the EHR usage data automatically recorded as clinicians navigated through the system's software user interface (UI) to perform different clinical tasks.

While our Y2K worries about old computers "retiring" at midnight captured the television and news media attention, a more significant "old age" phenomenon snuck onto the scene with hardly a headline: the dawn of the age of the aged. (1) The over burdened health care system will face a worldwide wave of retirees who will live longer, cost more to treat, and demand new goods and services to help them [...]

In public health and health services research, the inclusion of geographic information in data sets is critical. Because of concerns over the re-identification of patients, data from small geographic areas are either suppressed or the geographic areas are aggregated into larger ones. Our objective is to estimate the population size cut-off at which a geographic area is sufficiently large so that no data suppression or further aggregation is necessary.

The purpose of this study was to evaluate the adequacy of the International Classification of Nursing Practice (1) (ICPN) Version 1.0 as a representational model for nursing assessment documentation.

To measure the uncertainty of temporal assertions like "3 weeks ago" in clinical texts.

The Core Content for Clinical Informatics defines the boundaries of the discipline and informs the Program Requirements for Fellowship Education in Clinical Informatics. The Core Content includes four major categories: fundamentals, clinical decision making and care process improvement, health information systems, and leadership and management of change. The AMIA Board of Directors approved the Core Content for Clinical Informatics in November 2008.