OBJECTIVE: We describe our approach to surveillance of reportable safety events captured in hospital data including free-text clinical notes. We hypothesize that a) some patient safety events are documented only in the clinical notes and not in any o...
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2022
Epidemiological studies identifying biological markers of disease state are valuable, but can be time-consuming, expensive, and require extensive intuition and expertise. Furthermore, not all hypothesized markers will be borne out in a study, suggest...
High-quality data are fundamental to healthcare research, future applications of artificial intelligence and advancing healthcare delivery and outcomes through a learning health system. Although routinely collected administrative health and electroni...
The journal of trauma and acute care surgery
Jan 1, 2022
INTRODUCTION: Patient outcome prediction models are underused in clinical practice because of lack of integration with real-time patient data. The electronic health record (EHR) has the ability to use machine learning (ML) to develop predictive model...
Natural language processing (NLP) is the task of converting unstructured human language data into structured data that a machine can understand. While its applications are far and wide in healthcare, and are growing considerably every day, this chapt...
OBJECTIVES: Existing methods for measuring adverse events in hospitals intercept a restricted number of events. Text mining refers to a range of techniques to extract data from narrative sources. The goal of this study was to evaluate the performance...
PURPOSE: The purpose of this article was to develop and validate a natural language processing (NLP) algorithm to extract qualitative descriptors of microbial keratitis (MK) from electronic health records.
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