Machine Learning
A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record.
Citation:
Wang L, Blackley SV, Blumenthal KG, Yerneni S, Goss FR, Lo YC, Shah SN, Ortega CA, Korach ZT, Seger DL, Zhou L. A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record. J Am Med Inform Assoc. 2020 Jun 1;27(6):917-923. doi: 10.1093/jamia/ocaa042. PMID: 32417930.
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A factored generalized additive model for clinical decision support in the operating room.
Citation:
Cui Z, Fritz BA, King CR, Avidan MS, Chen Y. A factored generalized additive model for clinical decision support in the operating room. AMIA Annu Symp Proc. 2020 Mar 4;2019:343-52. PMID 32308827.
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Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST) - Final Report
Citation:
Avidan M. Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST) - Final Report. (Prepared by the University of Utah under Grant No. R21 HS024581). Rockville, MD: Agency for Healthcare Research and Quality, 2020.
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Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery.
Citation:
Liu L, Ni Y, Zhang N, Nick Pratap J. Mining patient-specific and contextual data with machine learning technologies to predict cancellation of children's surgery. Int J Med Inform. 2019 Sep;129:234-241. doi:
10.1016/j.ijmedinf.2019.06.007. Epub 2019 Jun 8. PMID: 31445261.
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Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation - Final Report
Citation:
Pratap J. Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation - Final Report. (Prepared by Cincinnati Children's Hospital Medical Center under Grant No. R21 HS024983). Rockville, MD: Agency for Healthcare Research and Quality, 2019.
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Semi-Automated Identification of Biomedical Literature
Description:
This research will develop and evaluate a semi-automatic approach to conducting literature searches for systematic reviews.
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Project Dates:
September 30, 2019 to September 29, 2020
NLP to Improve Accuracy and Quality of Dictated Medical Documents - Final Report
Citation:
Zhou L. NLP to Improve Accuracy and Quality of Dictated Medical Documents - Final Report. (Prepared by Brigham and Women's Hospital under Grant No. R01 HS024264). Rockville, MD: Agency for Healthcare Research and Quality, 2019.
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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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Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients - Final Report
Citation:
Dexheimer J. Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients - Final Report. (Prepared by Cincinnati Children's Hospital Medical Center under Grant No. R21 HS024977). Rockville, MD: Agency for Healthcare Research and Quality, 2018.
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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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