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|Title:||Association patterns of ontological features signify electronic health records in liver cancer||Authors:||Chan, LWC
|Issue Date:||2017||Publisher:||Hindawi Publishing Corporation||Source:||Journal of healthcare engineering, 2017, 6493016 How to cite?||Journal:||Journal of healthcare engineering||Abstract:||Electronic Health Record (EHR) system enables clinical decision support. In this study, a set of 112 abdominal computed tomography imaging examination reports, consisting of 59 cases of hepatocellular carcinoma (HCC) or liver metastases (so-called HCC group for simplicity) and 53 cases with no abnormality detected (NAD group), were collected from four hospitals in Hong Kong. We extracted terms related to liver cancer from the reports and mapped them to ontological features using Systematized Nomenclature of Medicine (SNOMED) Clinical Terms (CT). The primary predictor panel was formed by these ontological features. Association levels between every two features in the HCC and NAD groups were quantified using Pearson's correlation coefficient. The HCC group reveals a distinct association pattern that signifies liver cancer and provides clinical decision support for suspected cases, motivating the inclusion of new features to form the augmented predictor panel. Logistic regression analysis with stepwise forward procedure was applied to the primary and augmented predictor sets, respectively. The obtained model with the new features attained 84.7% sensitivity and 88.4% overall accuracy in distinguishing HCC from NAD cases, which were significantly improved when compared with that without the new features.||URI:||http://hdl.handle.net/10397/76507||ISSN:||2040-2295||EISSN:||2040-2309||DOI:||10.1155/2017/6493016||Rights:||Copyright © 2017 Lawrence W. C. Chan et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following article: Lawrence W. C. Chan, S. C. Cesar Wong, Choo Chiap Chiau, et al., “Association Patterns of Ontological Features Signify Electronic Health Records in Liver Cancer,” Journal of Healthcare Engineering, vol. 2017, Article ID 6493016, 9 pages, 2017 is available at https://doi.org/10.1155/2017/6493016.
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