AJR. American journal of roentgenology
Jan 30, 2019
OBJECTIVE: Radiology reports are rich resources for biomedical researchers. Before utilization of radiology reports, experts must manually review these reports to identify the categories. In fact, automatically categorizing electronic medical record ...
Current approaches to predicting a cardiovascular disease (CVD) event rely on conventional risk factors and cross-sectional data. In this study, we applied machine learning and deep learning models to 10-year CVD event prediction by using longitudina...
OBJECTIVE: The In-hospital length of stay (LOS) is expected to increase as cardiovascular diseases complexity increases and the population ages. This will affect healthcare systems especially with the current situation of decreased bed capacity and i...
BACKGROUND: A Cardiac-centered Frailty Ontology can be an important foundation for using NLP to assess patient frailty. Frailty is an important consideration when making patient treatment decisions, particularly in older adults, those with a cardiac ...
Operating room (OR) utilization is a significant determinant of hospital profitability. One aspect of this is surgical scheduling, which depends on accurate predictions of case duration. This has been done historically by either the surgeon based on ...
Computer methods and programs in biomedicine
Jan 12, 2019
BACKGROUND AND OBJECTIVE: Electronic Health Record (EHR) data often include observation records that are unlikely to represent the "truth" about a patient at a given clinical encounter. Due to their high throughput, examples of such implausible obser...
BMC medical informatics and decision making
Jan 10, 2019
BACKGROUND: Adverse drug events (ADEs) as well as other preventable adverse events in the hospital setting incur a yearly monetary cost of approximately $3.5 billion, in the United States alone. Therefore, it is of paramount importance to reduce the ...
BACKGROUND: Natural language processing (NLP) of health-related data is still an expertise demanding, and resource expensive process. We created a novel, open source rapid clinical text mining system called NimbleMiner. NimbleMiner combines several m...
BMC medical informatics and decision making
Jan 9, 2019
BACKGROUND: Main adverse cardiac events (MACE) are essentially composite endpoints for assessing safety and efficacy of treatment processes of acute coronary syndrome (ACS) patients. Timely prediction of MACE is highly valuable for improving the effe...
International journal of medical informatics
Jan 7, 2019
AIMS: To develop a natural language processing (NLP)-based algorithm for extracting clinically useful information for patients with hepatocellular carcinoma (HCC) from Chinese electronic medical records (EMRs) and use these data for the assessment of...
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