BMC medical informatics and decision making
Feb 28, 2019
BACKGROUND: Life expectancy is one of the most important factors in end-of-life decision making. Good prognostication for example helps to determine the course of treatment and helps to anticipate the procurement of health care services and facilitie...
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼...
Electronic health record (EHR) data provide promising opportunities to explore personalized treatment regimes and to make clinical predictions. Compared with regular clinical data, EHR data are known for their irregularity and complexity. In addition...
Clinical named entity recognition aims to identify and classify clinical terms such as diseases, symptoms, treatments, exams, and body parts in electronic health records, which is a fundamental and crucial task for clinical and translational research...
Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment of many disorders including hypertension, obesity, and diabetes. Lifestyle modification data are not easily retrieved or used in research due to thei...
Normalization of clinical text involves linking different ways of talking about the same clinical concept to the same term in the standardized vocabulary. To date, very few annotated corpora for normalization have been available, and existing corpora...
BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data...
International journal of medical informatics
Feb 20, 2019
OBJECTIVE: In this systematic review, we aim to synthesize the literature on the use of natural language processing (NLP) and text mining as they apply to symptom extraction and processing in electronic patient-authored text (ePAT).
Psychiatric services (Washington, D.C.)
Feb 20, 2019
An unprecedented amount of clinical information is now available via electronic health records (EHRs). These massive data sets have stimulated opportunities to adapt computational approaches to track and identify target areas for quality improvement ...
OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity to address the pressing public health problem of adolescent suicidal behavior. We describe the devel...
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