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Machine Learning
Machine Learning
Exploration and initial development of text classification models to identify health information technology usability-related patient safety event reports.
Citation:
Fong A, Komolafe T, Adams KT, Cohen A, Howe JL, Ratwani RM. Exploration and initial development of text classification models to identify health information technology usability-related patient safety event reports. Appl Clin Inform. 2019 May;10(3):521-527. doi: 10.1055/s-0039-1693427. Epub 2019 Jul 17. PMID: 31315139.
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Health Information Technology in Heart Failure Care - Final Report
Citation:
Blecker S. Health Information Technology in Heart Failure Care - Final Report. (Prepared by the New York University School of Medicine under Grant No. K08 HS023683). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
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Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report
Citation:
Sherwin R. Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report. (Prepared by Wayne State University under Grant No. R21 HS024750). Rockville, MD: Agency for Healthcare Research and Quality, 2019.
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Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report
Citation:
Goss F. Natural Language Processing to Identify and Rank Clinically Relevant Information for EHRs in the Emergency Department - Final Report. (Prepared by the University of Colorado under Grant No. R21 HS024541). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
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HopScore: an Electronic Outcomes-Based Emergency Triage System - Final Report
Citation:
Levin, S. HopScore: an Electronic Outcomes-Based Emergency Triage System - Final Report. (Prepared by Johns Hopkins University under Grant No. R21 HS023641). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
Principal Investigator:
Improving Missing Data Analysis in Distributed Research Networks
Description:
This project aims to refine and develop methods to address missing electronic health record data to improve data quality and research validity.
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Project Dates:
September 30, 2018 to September 29, 2021
TREAT ECARDS: Translating Evidence into Action: Electronic Clinical Decision Support in ARDS
Description:
This project will develop and evaluate an electronic clinical decision support tool for care of patients with Acute Respiratory Distress Syndrome.
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Project Dates:
September 1, 2018 to June 30, 2021
Identifying health information technology related safety event reports from patient safety event report databases.
Citation:
Fong A, Adams KT, Gaunt MJ, et al. Identifying health information technology related safety event reports from patient safety event report databases. J Biomed Inform 2018 Oct;86:135-142. Epub 2018 Sep 10. PMID: 30213556.
Principal Investigator:
The impact of risk standardization on variation in CT Use and emergency physician profiling.
Citation:
Taylor RA, Melnick E, Fleishman W, et al. The impact of risk standardization on variation in CT Use and emergency physician profiling. AJR Am J Roentgenol 2018 Aug;211(2):392-399. Epub 2018 Jul 5. PMID: 29975119.
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Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study.
Citation:
Fritz BA, Chen Y, Murray-Torres TM, et al. Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study. BMJ Open 2018 Apr 10;8(4):e020124. PMID: 29643160.
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