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Biomedical research has and will continue to generate large amounts of data (termed 'big data') in many formats and at all levels. Consequently, there is an increasing need to better understand and mine the data to further knowledge and foster new discovery. The National Institutes of Health (NIH) has initiated a Big Data to Knowledge (BD2K) initiative to maximize the use of biomedical big data. BD2K seeks to better define [...]

To determine whether assisted annotation using interactive training can reduce the time required to annotate a clinical document corpus without introducing bias.

Pathology reports are rich in narrative statements that encode a complex web of relations among medical concepts. These relations are routinely used by doctors to reason on diagnoses, but often require hand-crafted rules or supervised learning to extract into prespecified forms for computational disease modeling. We aim to automatically capture relations from narrative text without supervision.

The outpatient clinical note documents the clinician's information collection, problem assessment, and patient management, yet there is currently no validated instrument to measure the quality of the electronic clinical note. This study evaluated the validity of the QNOTE instrument, which assesses 12 elements in the clinical note, for measuring the quality of clinical notes. It also compared its performance with a global instrument that assesses the clinical note as a [...]

To examine the impact of a personal health record (PHR) on medication-use safety among older adults.

The constant progress in computational linguistic methods provides amazing opportunities for discovering information in clinical text and enables the clinical scientist to explore novel approaches to care. However, these new approaches need evaluation. We describe an automated system to compare descriptions of epilepsy patients at three different organizations: Cincinnati Children's Hospital, the Children's Hospital Colorado, and the Children's Hospital of Philadelphia. To our knowledge, there have been no similar previous [...]

Record linkage to integrate uncoordinated databases is critical in biomedical research using Big Data. Balancing privacy protection against the need for high quality record linkage requires a human-machine hybrid system to safely manage uncertainty in the ever changing streams of chaotic Big Data.