Joe Kesterson

TL;DR: In this article, a negation detection algorithm, NegEx, applies a simplistic approach that has been shown to be powerful in clinical NLP, but due to the failure to consider the contextual relationship between words within a sentence, negEx fails to correctly capture the negation status of concepts in complex sentences.

TL;DR: Discharge summaries are grossly inadequate at documenting both tests with pending results and the appropriate follow-up providers.

TL;DR: Several variables influencing the accuracy of ICD-9 codes to identify cancer patients including: the identification algorithm, kind of cancer to be identified, presence of other conditions similar to cancer, and presence of conditions that are precancerous are identified.

TL;DR: In this article, the authors defined a variability measure that is independent of change over time and determine the association between longitudinal summary measures of BP measurements and mortality risk, and demonstrated in this elderly primary care patient population that BP changes over time, not variability, were associated with greater mortality risk.

TL;DR: Natural language processing is a reliable and accurate method for identifying selected patient cohorts and may facilitate the identification and follow-up of patients with IPMN.