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Natural language processing (NLP) tasks are commonly decomposed into subtasks, chained together to form processing pipelines. The residual error produced in these subtasks propagates, adversely affecting the end objectives. Limited availability of annotated clinical data remains a barrier to reaching state-of-the-art operating characteristics using statistically based NLP tools in the clinical domain. Here we explore the unique linguistic constructions of clinical texts and demonstrate the loss in operating characteristics when [...]

To create an end-to-end system to identify temporal relation in discharge summaries for the 2012 i2b2 challenge. The challenge includes event extraction, timex extraction, and temporal relation identification.

Prognostic studies of breast cancer survivability have been aided by machine learning algorithms, which can predict the survival of a particular patient based on historical patient data. However, it is not easy to collect labeled patient records. It takes at least 5 years to label a patient record as 'survived' or 'not survived'. Unguided trials of numerous types of oncology therapies are also very expensive. Confidentiality agreements with doctors and [...]

To explore how key components of economic evaluations have been included in evaluations of health information systems (HIS), to determine the state of knowledge on value for money for HIS, and provide guidance for future evaluations.

To evaluate the validity of, characterize the usage of, and propose potential research applications for International Classification of Diseases, Ninth Revision (ICD-9) tobacco codes in clinical populations.

Allergy documentation and exchange are vital to ensuring patient safety. This study aims to analyze and compare various existing standard terminologies for representing allergy information.

Epistasis has been historically used to describe the phenomenon that the effect of a given gene on a phenotype can be dependent on one or more other genes, and is an essential element for understanding the association between genetic and phenotypic variations. Quantifying epistasis of orders higher than two is very challenging due to both the computational complexity of enumerating all possible combinations in genome-wide data and the lack of [...]

Temporal information detection systems have been developed by the Mayo Clinic for the 2012 i2b2 Natural Language Processing Challenge.

Detecting complex patterns of association between genetic or environmental risk factors and disease risk has become an important target for epidemiological research. In particular, strategies that provide multifactor interactions or heterogeneous patterns of association can offer new insights into association studies for which traditional analytic tools have had limited success.