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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 [...]

This study was to assess whether active learning strategies can be integrated with supervised word sense disambiguation (WSD) methods, thus reducing the number of annotated samples, while keeping or improving the quality of disambiguation models.

Clinical documentation is central to the medical record and so to a range of healthcare and business processes. As electronic health record adoption expands, computerized provider documentation (CPD) is increasingly the primary means of capturing clinical documentation. Previous CPD studies have focused on particular stakeholder groups and sites, often limiting their scope and conclusions. To address this, we studied multiple stakeholder groups from multiple sites across the USA.

The goal of this work was to evaluate machine learning methods, binary classification and sequence labeling, for medication-attribute linkage detection in two clinical corpora.

To characterize question types that residents received on overnight shifts and what information sources were used to answer them.

To determine how well statistical text mining (STM) models can identify falls within clinical text associated with an ambulatory encounter.

To assess patients' desire for granular level privacy control over which personal health information should be shared, with whom, and for what purpose; and whether these preferences vary based on sensitivity of health information.

To test the feasibility of using text mining to depict meaningfully the experience of pain in patients with metastatic prostate cancer, to identify novel pain phenotypes, and to propose methods for longitudinal visualization of pain status.