The purpose of this study was to use natural language processing of physician documentation to predict mortality in patients admitted to the surgical intensive care unit (SICU). The Multiparameter Intelligent Monitoring in Intensive Care III database...
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2018
OBJECTIVE: To automatically recognize self-acknowledged limitations in clinical research publications to support efforts in improving research transparency.
OBJECTIVES: Early prediction of undesired outcomes among newly hospitalized patients could improve patient triage and prompt conversations about patients' goals of care. We evaluated the performance of logistic regression, gradient boosting machine, ...
Journal of the American Medical Informatics Association : JAMIA
Jul 1, 2018
OBJECTIVE: Medical word sense disambiguation (WSD) is challenging and often requires significant training with data labeled by domain experts. This work aims to develop an interactive learning algorithm that makes efficient use of expert's domain kno...
Administration and policy in mental health
Jul 1, 2018
To derive a method of identifying use of evidence-based psychotherapy (EBP) for post-traumatic stress disorder (PTSD), we used clinical note text from national Veterans Health Administration (VHA) medical records. Using natural language processing, w...
Journal of the American Medical Informatics Association : JAMIA
Jun 1, 2018
OBJECTIVE: Distributional semantics algorithms, which learn vector space representations of words and phrases from large corpora, identify related terms based on contextual usage patterns. We hypothesize that distributional semantics can speed up lex...
This study introduces the second release of the Tool for the Automatic Analysis of Lexical Sophistication (TAALES 2.0), a freely available and easy-to-use text analysis tool. TAALES 2.0 is housed on a user's hard drive (allowing for secure data proce...
Journal of the American Medical Informatics Association : JAMIA
May 1, 2018
OBJECTIVE: Unlocking the data contained within both structured and unstructured components of electronic health records (EHRs) has the potential to provide a step change in data available for secondary research use, generation of actionable medical i...
MOTIVATION: Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used t...
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