Mary Regina Boland

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OBJECTIVE To develop a semantic representation for clinical research eligibility criteria to automate semistructured information extraction from eligibility criteria text. MATERIALS AND METHODS An analysis pipeline called eligibility criteria extraction and representation (EliXR) was developed that integrates syntactic parsing and tree pattern mining to(More)
OBJECTIVES To automatically identify and cluster clinical trials with similar eligibility features. METHODS Using the public repository as the data source, we extracted semantic features from the eligibility criteria text of all clinical trials and constructed a trial-feature matrix. We calculated the pairwise similarities for all(More)
Clinical trial eligibility criteria define fine-grained characteristics of research volunteers for various disease trials and hence are a promising data source for disease profiling. This paper explores the feasibility of using disease-specific common eligibility features (CEFs) for representing diseases and understanding their relatedness. We extracted(More)
Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation(More)
The burgeoning adoption of electronic health records (EHR) introduces a golden opportunity for studying individual manifestations of myriad diseases, which is called 'EHR phenotyping'. In this paper, we break down this concept by: relating it to phenotype definitions from Johannsen; comparing it to cohort identification and disease subtyping; introducing a(More)
Phenotypes have gained increased notoriety in the clinical and biological domain owing to their application in numerous areas such as the discovery of disease genes and drug targets, phylogenetics and pharmacogenomics. Phenotypes, defined as observable characteristics of organisms, can be seen as one of the bridges that lead to a translation of experimental(More)
OBJECTIVE An individual's birth month has a significant impact on the diseases they develop during their lifetime. Previous studies reveal relationships between birth month and several diseases including atherothrombosis, asthma, attention deficit hyperactivity disorder, and myopia, leaving most diseases completely unexplored. This retrospective population(More)
Underspecified user needs and frequent lack of a gold standard reference are typical barriers to technology evaluation. To address this problem, this paper presents a two-phase evaluation framework involving usability experts (phase 1) and end-users (phase 2). In phase 1, a cross-system functionality alignment between expert-derived user needs and system(More)
To most medical researchers, databases are obscure black boxes. Query analysts are often indispensable guides aiding researchers to perform mediated data queries. However, this approach does not scale up and is time-consuming and expensive. We analyzed query mediation dialogues to inform future designs of intelligent query mediation systems. Thirty-one(More)
Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure. Epidemiologists often measure these changes using birth month as a proxy for seasonal variance. Likewise, Genome-Wide Association Studies have associated or implicated these same diseases with many genes. Both disparate data(More)