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Natural Language Processing System
Natural Language Processing System
Identification of Patients with Low Life Expectancy - Final Report
Citation:
Turchin A. Identification of Patients with Low Life Expectancy - Final Report. (Prepared by Cincinnati Children's Hospital Medical Center under Grant No. R21 HS024977). Rockville, MD: Agency for Healthcare Research and Quality, 2019.
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Real-time Assessment of Dialogue in Motivational Interviewing Training (ReadMI)
Description:
This research will enhance and test a tool which uses natural language processing to provide a real-time assessment of dialog during motivational interviewing training.
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Project Dates:
August 1, 2019 to July 31, 2021
Semi-Automated Identification of Biomedical Literature
Description:
This research will develop and evaluate a semi-automatic approach to conducting literature searches for systematic reviews.
Principal Investigator:
Project Dates:
September 30, 2019 to September 29, 2020
Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.
Citation:
Wissel BD, Greiner HM, Glauser TA, Holland-Bouley KD, Mangano FT, Santel D, Faist R, Zhang N, Pestian JP, Szczesniak RD, Dexheimer JW. Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery. Epilepsia. 2019 Nov 29. doi: 10.1111/epi.16398. [Epub ahead of print]. PMID: 31784992.
Principal Investigator:
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Citation:
Wissel BD, Greiner HM, Glauser TA, Mangano FT, Santel D, Pestian JP, Szczesniak RD, Dexheimer JW. Investigation of bias in an epilepsy machine learning algorithm trained on physician notes. Epilepsia. 2019 Sep;60(9):e93-e98. doi: 10.1111/epi.16320. Epub 2019 Aug 23. PMID: 31441044.
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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.
Principal Investigator:
How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions.
Citation:
Salazar A, Karmiy SJ, Forsythe KJ, Amato MG, Wright A, Lai KH, Lambert BL, Liebovitz DM, Eguale T, Volk LA, Schiff GD. How often do prescribers include indications in drug orders? Analysis of 4 million outpatient prescriptions. Am J Health Syst Pharm. 2019 Jun 18;76(13):970-979. doi: 10.1093/ajhp/zxz082. PMID: 31361884.
Principal Investigator:
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.
Principal Investigator:
Quality of documentation of contrast agent allergies in electronic health records.
Citation:
Deng F, Li MD, Wong A, Kowalski LT, Lai KH, Digumarthy SR, Zhou L. Quality of documentation of contrast agent allergies in electronic health records. J Am Coll Radiol. 2019 Aug;16(8):1027-1035. doi: 10.1016/j.jacr.2019.01.027. Epub 2019 Mar 4. PMID: 30846398.
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