Consensus Development of a Modern Ontology of Emergency Department Presenting Problems-The Hierarchical Presenting Problem Ontology (HaPPy).
暂无分享,去创建一个
Steven Horng | Nathaniel R Greenbaum | Larry A Nathanson | James C McClay | Foster R Goss | Jeffrey A Nielson
[1] H. Kirchner,et al. Identifying Asthma Exacerbation-Related Emergency Department Visit Using Electronic Medical Record and Claims Data , 2018, Applied Clinical Informatics.
[2] Helen Burstin,et al. Quality measurement in the emergency department: past and future. , 2013, Health affairs.
[3] E. Hess,et al. Electronic medical records and physician stress in primary care: results from the MEMO Study. , 2014, Journal of the American Medical Informatics Association : JAMIA.
[4] A V Gundlapalli,et al. Development and Validation of a Natural Language Processing Tool to Identify Patients Treated for Pneumonia across VA Emergency Departments , 2018, Applied Clinical Informatics.
[5] Sandra Kane-Gill,et al. Automated Screening of Emergency Department Notes for Drug-Associated Bleeding Adverse Events Occurring in Older Adults , 2017, Applied Clinical Informatics.
[6] Michael M. Wagner,et al. Technical Description of RODS: A Real-time Public Health Surveillance System , 2003, Journal of the American Medical Informatics Association.
[7] Li Zhou,et al. Mapping Partners Master Drug Dictionary to RxNorm using an NLP-based approach , 2012, J. Biomed. Informatics.
[8] James J. Cimino,et al. In defense of the Desiderata , 2005, Journal of Biomedical Informatics.
[9] Indra Neil Sarkar,et al. Health Information Exchange in Emergency Medical Services , 2018, Applied Clinical Informatics.
[10] Arvind Venkat,et al. Evaluation of a hospital admission prediction model adding coded chief complaint data using neural network methodology , 2015, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.
[11] D. L. Roberts,et al. A national comparison of burnout and work-life balance among internal medicine hospitalists and outpatient general internists. , 2014, Journal of hospital medicine.
[12] Roger Collier,et al. Rethinking EHR interfaces to reduce click fatigue and physician burnout , 2018, Canadian Medical Association Journal.
[13] George Hripcsak,et al. Clinical Information Systems Integration in New York City's First Mobile Stroke Unit , 2018, Applied Clinical Informatics.
[14] Debbie A. Travers,et al. Evaluation of preprocessing techniques for chief complaint classification , 2008, J. Biomed. Informatics.
[15] Robert Arp,et al. Building Ontologies with Basic Formal Ontology , 2015 .
[16] Randolph A. Miller,et al. Review Paper: Interface Terminologies: Facilitating Direct Entry of Clinical Data into Electronic Health Record Systems , 2006, J. Am. Medical Informatics Assoc..
[17] Blackford Middleton,et al. Evaluating standard terminologies for encoding allergy information , 2013, J. Am. Medical Informatics Assoc..
[18] H Kenneth Walker,et al. Clinical methods: The history, physical, and laboratory examinations , 1976 .
[19] J Silva,et al. Comparison of two major emergency department-based free-text chief-complaint coding systems. , 2004, MMWR supplements.
[20] Aileen Schast,et al. Standardizing Care Processes and Improving Quality Using Pathways and Continuous Quality Improvement , 2015, Current Treatment Options in Pediatrics.
[21] Lalit Bajaj,et al. The Pediatric Emergency Care Applied Research Network Registry: A Multicenter Electronic Health Record Registry of Pediatric Emergency Care , 2018, Applied Clinical Informatics.
[22] Stephanie W. Haas,et al. Toward vocabulary control for chief complaint. , 2008, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[23] Larry A. Nathanson,et al. Contextual Autocomplete: A Novel User Interface Using Machine Learning to Improve Ontology Usage and Structured Data Capture for Presenting Problems in the Emergency Department , 2017 .
[24] David A Thompson,et al. Coded Chief Complaints--automated analysis of free-text complaints. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[25] Daniel A Pollock,et al. Data Elements for Emergency Department Systems, Release 1.0 (DEEDS): A Summary Report. , 1998, Annals of emergency medicine.
[26] Ye Ye,et al. The effects of natural language processing on cross-institutional portability of influenza case detection for disease surveillance , 2017, Applied Clinical Informatics.
[27] Benjamin A. Lopman,et al. Emergency Department Visit Data for Rapid Detection and Monitoring of Norovirus Activity, United States , 2013, Emerging infectious diseases.
[28] W. Chapman,et al. Syndrome and outbreak detection using chief-complaint data--experience of the Real-Time Outbreak and Disease Surveillance project. , 2004, MMWR supplements.
[29] Wendy W Chapman,et al. Classification of emergency department chief complaints into 7 syndromes: a retrospective analysis of 527,228 patients. , 2005, Annals of emergency medicine.
[30] Samuli Niiranen,et al. Toward Reflective Management of Emergency Department Chief Complaint Information , 2008, IEEE Transactions on Information Technology in Biomedicine.
[31] Stephanie W. Haas,et al. Unified medical language system coverage of emergency-medicine chief complaints. , 2006, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[32] Christopher Beach,et al. Chief complaint-based performance measures: a new focus for acute care quality measurement. , 2015, Annals of emergency medicine.
[33] P J Haug,et al. A comprehensive set of coded chief complaints for the emergency department. , 2001, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.
[34] Donald Macfarlane. The lexeme hypotheses: Their use to generate highly grammatical and completely computerized medical records. , 2016, Medical hypotheses.
[35] Shital C. Shah,et al. Comparing the accuracy of syndrome surveillance systems in detecting influenza-like illness: GUARDIAN vs. RODS vs. electronic medical record reports , 2013, Artif. Intell. Medicine.
[36] Frank Naeymi-Rad,et al. Problem-centered care delivery: how interface terminology makes standardized health information possible. , 2012, Journal of AHIMA.
[37] Michelle Daniel,et al. Cognitive Debiasing Strategies for the Emergency Department , 2017, AEM education and training.
[38] Pat Croskerry,et al. Cognitive forcing strategies in clinical decisionmaking. , 2003, Annals of emergency medicine.
[39] William R. Hogan,et al. Natural Language Processing methods and systems for biomedical ontology learning , 2011, J. Biomed. Informatics.
[40] Abigail R. Wooldridge,et al. Physician Perceptions of the Electronic Problem List in Pediatric Trauma Care , 2019, Applied Clinical Informatics.