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Natural Language Processing System
Natural Language Processing System
Building the evidence-base to reduce electronic health record-related clinician burden.
Citation:
Dymek C, Kim B, Melton GB, Payne TH, Singh H, Hsiao CJ. Building the evidence-base to reduce electronic health record-related clinician burden. J Am Med Inform Assoc. 2021 Apr 23;28(5):1057-1061. doi: 10.1093/jamia/ocaa238. PMID: 33340326; PMCID: PMC8068419.
Principal Investigator:
Project Name:
Optimizing corpus creation for training word embedding in low resource domains: a case study in Autism Spectrum Disorder (ASD).
Citation:
Gu Y, Leroy G, Pettygrove S, Galindo MK, Kurzius-Spencer M. Optimizing corpus creation for training word embedding in low resource domains: a case study in Autism Spectrum Disorder (ASD). AMIA Annu Symp Proc. 2018 Dec 5;2018:508-517. PMID: 30815091.
Principal Investigator:
Enabling Large-Scale Research on Autism Spectrum Disorders Through Automated Processing of EHR Using Natural Language Understanding - Final Report
Citation:
Leroy G. Enabling Large-Scale Research on Autism Spectrum Disorders Through Automated Processing of EHR Using Natural Language Understanding - Final Report. (Prepared by the University Of Arizona under Grant No. R21 HS024988). Rockville, MD: Agency for Healthcare Research and Quality, 2020.
Principal Investigator:
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.
Principal Investigator:
Project Name:
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.
Principal Investigator:
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.
Principal Investigator:
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:
