NDLI: Use of Neural Networks to Predict Adverse Outcomes from Acute Coronary Syndrome for Male and Female Patients

Content Provider	IEEE Xplore Digital Library
Author	McCullough, C.L. Novobilski, A.J. Fesmire, F.M.
Copyright Year	2007
Description	Author affiliation: Univ. of Tennessee, Chattanooga (McCullough, C.L.; Novobilski, A.J.)
Abstract	Neural networks have been used to examine a set of thirteen objective features and a single subjective physician's assessment for emergency room patients with symptoms possibly indicative of acute coronary syndrome (ACS). The objective data is information routinely collected during triage. The neural networks were used to fuse the disparate types of information with the goal of forecasting thirty-day adverse patient outcome. Results were evaluated using receiver operating characteristic curves describing the outcomes of the nets, both using only objective features and including the subjective physician's assessment. These results, based on all patient data, are compared to those obtained using neural networks trained on information from male and female patients separately. While preliminary, the results of this continuing study are significant from the perspective of potential use of the intelligent fusion of biomedical informatics to aid the physician in prescribing treatment necessary to prevent serious adverse outcome from ACS.
Starting Page	512
Ending Page	517
File Size	610547
Page Count	6
File Format	PDF
ISBN	9780769530697
DOI	10.1109/ICMLA.2007.40
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart Pain Neural networks Biomedical informatics Myocardium Muscles Educational institutions Medical diagnostic imaging Blood Arteries
Content Type	Text
Resource Type	Article

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