Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Amanda I. Messinger"'
Publikováno v:
IEEE Access, Vol 8, Pp 195971-195979 (2020)
Asthma puts a tremendous overhead on healthcare. To enable effective preventive care to improve outcomes in managing asthma, we recently created two machine learning models, one using University of Washington Medicine data and the other using Intermo
Externí odkaz:
https://doaj.org/article/9b1b9035277344b1a4a2f43ff428dca0
Autor:
Robin R. Deterding, Nam Bui, Amanda I. Messinger, Tam Vu, Brandie D. Wagner, Stanley J. Szefler
Publikováno v:
Pediatr Pulmonol
OBJECTIVES Manual clinical scoring systems are the current standard used for acute asthma clinical care pathways. No automated system exists that assesses disease severity, time course, and treatment impact in pediatric acute severe asthma exacerbati
Autor:
Giana H. Davidson, Amanda I. Messinger, Gang Luo, Adam B. Wilcox, Yao Tong, Sean D. Mooney, Pradeep Suri
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 4, p e22796 (2021)
Journal of Medical Internet Research
Journal of Medical Internet Research
Background Asthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations and emergency department visits every year. To lower the number of such encounters, many health care systems and heal
Publikováno v:
IEEE Access
Asthma puts a tremendous overhead on healthcare. To enable effective preventive care to improve outcomes in managing asthma, we recently created two machine learning models, one using University of Washington Medicine data and the other using Intermo
Autor:
Zfania Tom Korach, Kelly Bookman, Li Zhou, Stephen C. Gradwohl, Foster R. Goss, Amanda I. Messinger, Kevin Bretonnel Cohen
Publikováno v:
International journal of medical informatics. 149
Decision making in the Emergency Department (ED) requires timely identification of clinical information relevant to the complaints. Existing information retrieval solutions for the electronic health record (EHR) focus on patient cohort identification
Autor:
Yao Tong, Amanda I Messinger, Adam B Wilcox, Sean D Mooney, Giana H Davidson, Pradeep Suri, Gang Luo
BACKGROUND Asthma affects a large proportion of the population and leads to many hospital encounters involving both hospitalizations and emergency department visits every year. To lower the number of such encounters, many health care systems and heal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b7ba33d1ba7346721c91d1af5684e56f
https://doi.org/10.2196/preprints.22796
https://doi.org/10.2196/preprints.22796
Publikováno v:
Pediatrics in review. 38(9)
1. Amanda I. Messinger, MD* 2. Oren Kupfer, MD* 3. Amanda Hurst, PharmD† 4. Sarah Parker, MD‡ 1. Divisions of *Pulmonary Medicine and 2. ‡Infectious Diseases, Department of Pediatrics, University of Colorado Denver School of Medicine, Aurora, C
Publikováno v:
American Journal of Respiratory and Critical Care Medicine. 198:291-292
Rationale: Asthma management depends on prompt identification of symptoms, which challenges both patients and providers. In asthma, a misapprehension of health between exacerbations can compromise compliance. Thus, there is a need for a tool that per