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To understand the factors that influence success in scrubbing personal names from narrative text.

An innovative web-based system was developed to allow patient-reported outcome measures (PROMs) to be easily administered. Stakeholders guided the design and implementation. The software gives patients access to their current and previous scores. This pilot study focused on patients undergoing arthroscopic subacromial decompression, evaluated using the Oxford shoulder score (OSS). Patients showing good improvement in their OSS were offered the choice to return for routine follow-up clinic appointments, or continue [...]

To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods.

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the 'Big Data' challenges facing the medical informatics community can be [...]

Understanding population-level health trends is essential to effectively monitor and improve public health. The Office of the National Coordinator for Health Information Technology (ONC) Query Health initiative is a collaboration to develop a national architecture for distributed, population-level health queries across diverse clinical systems with disparate data models. Here we review Query Health activities, including a standards-based methodology, an open-source reference implementation, and three pilot projects.

On July 1, 2012 Australia launched a personally controlled electronic health record (PCEHR) designed around the needs of consumers. Using a distributed model and leveraging key component national eHealth infrastructure, the PCEHR is designed to enable sharing of any health information about a patient with them and any other health practitioner involved in their care to whom the patient allows access. This paper discusses the consumer-facing part of the program.

Natural language processing (NLP) applications typically use regular expressions that have been developed manually by human experts. Our goal is to automate both the creation and utilization of regular expressions in text classification.

Data-driven risk stratification models built using data from a single hospital often have a paucity of training data. However, leveraging data from other hospitals can be challenging owing to institutional differences with patients and with data coding and capture.

As large genomics and phenotypic datasets are becoming more common, it is increasingly difficult for most researchers to access, manage, and analyze them. One possible approach is to provide the research community with several petabyte-scale cloud-based computing platforms containing these data, along with tools and resources to analyze it.