Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Haijun Zhai"'
Autor:
Huaxiu Tang, Eric S. Kirkendall, Todd Lingren, Jaroslaw Meller, Yizhao Ni, Haijun Zhai, Imre Solti
Publikováno v:
Biomedical Informatics Insights, Vol 9 (2017)
Biomedical Informatics Insights
Biomedical Informatics Insights
The objective of this study was to determine whether the Food and Drug Administration’s Adverse Event Reporting System (FAERS) data set could serve as the basis of automated electronic health record (EHR) monitoring for the adverse drug reaction (A
Autor:
Huaxiu Tang, Imre Solti, Constance McAneney, Qi Li, Haijun Zhai, Todd Lingren, Judith W. Dexheimer, Yizhao Ni, Stephanie Kennebeck
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objectives (1) To develop an automated eligibility screening (ES) approach for clinical trials in an urban tertiary care pediatric emergency department (ED); (2) to assess the effectiveness of natural language processing (NLP), information extraction
Autor:
Haijun Zhai, Eric S. Hall, Kristin R. Melton, Laura Stoutenborough, Todd Lingren, Eric S. Kirkendall, Qi Li, Imre Solti, Yizhao Ni, Megan Kaiser
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Background Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the neon
Autor:
Qi Li, Eric S. Kirkendall, Todd Lingren, Haijun Zhai, Louise Deléger, Holly Brodzinski, Imre Solti, Evaline A. Alessandrini
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective To evaluate a proposed natural language processing (NLP) and machine-learning based automated method to risk stratify abdominal pain patients by analyzing the content of the electronic health record (EHR). Methods We analyzed the EHRs of a
Autor:
Imre Solti, Megan Kaiser, Qi Li, Todd Lingren, Louise Deléger, Haijun Zhai, Katalin Molnar, Laura Stoutenborough, Jareen Meinzen-Derr
Publikováno v:
Journal of the American Medical Informatics Association : JAMIA
Objective To present a series of experiments: (1) to evaluate the impact of pre-annotation on the speed of manual annotation of clinical trial announcements; and (2) to test for potential bias, if pre-annotation is utilized. Methods To build the gold
Publikováno v:
Plant Cell, Tissue and Organ Culture. 87:321-327
Plants were regenerated from mesophyll protoplasts of Ipomoea cairica L., a wild relative of sweetpotato (Ipomoea batatas (L.) Lam.), and somatic hybrids between I. cairica L. and sweetpotato cv. Xushu 18 were obtained by PEG-mediated method. I. cair
Publikováno v:
Acta Horticulturae. :81-85
Publikováno v:
In Vitro Cellular & Developmental Biology - Plant. 37:564-567
Using 15 Chinese and Japanese cultivars of sweetpotato, Ipomoea batatas (L.) Lam., we succeeded in developing an efficient plant regeneration system from embryogenic suspension cultures. The embryogenic callus derived from shoot apices of the 15 cult
Autor:
David Solti, Haijun Zhai
Publikováno v:
BCB
Our null hypothesis was that a computer algorithm will not predict breast cancer patients' 10-year survival with greater accuracy than the 64.3% baseline of the Surveillance Epidemiology and End Results (SEER) database [3]. The aims of this study wer
Autor:
Todd Lingren, Imre Solti, Laura Stoutenborough, Megan Kaiser, Qi Li, Haijun Zhai, Louise Deléger
Publikováno v:
Journal of Medical Internet Research
Journal of Medical Internet Research, Vol 15, Iss 4, p e73 (2013)
Journal of Medical Internet Research, Vol 15, Iss 4, p e73 (2013)
Background: A high-quality gold standard is vital for supervised, machine learning-based, clinical natural language processing (NLP) systems. In clinical NLP projects, expert annotators traditionally create the gold standard. However, traditional ann