Artificial Intelligence

Deep-learning model for predicting 30-day postoperative mortality.

Citation: 
Fritz BA, Cui Z, Zhang M, He Y, Chen Y, Kronzer A, Ben Abdallah A, King CR, Avidan MS. Deep-learning model for predicting 30-day postoperative mortality. Br J Anaesth. 2019 Nov;123(5):688-695. doi: 10.1016/j.bja.2019.07.025. Epub 2019 Sep 23. PMID: 31558311; PMCID: PMC6993109.
Principal Investigator: 
Avidan, Michael
Project Name: 
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

Study protocol for the implementation of the Gabby Preconception Care System - an evidence-based, health information technology intervention for Black and African American women.

Citation: 
Walter AW, Julce C, Sidduri N, Yinusa-Nyahkoon L, Howard J, Reichert M, Bickmore T, Jack BW. Study protocol for the implementation of the Gabby Preconception Care System - an evidence-based, health information technology intervention for Black and African American women. BMC Health Serv Res. 2020 Sep 21;20(1):889. doi: 10.1186/s12913-020-05726-0. PMID: 32958031; PMCID: PMC7504872.
Principal Investigator: 
Jack, Brian
Project Name: 
Implementation and Dissemination of 'Gabby,' a Health Information Technology System for Young Women, into Community-Based Clinical Sites

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: 
Leroy, Gondy
Project Name: 
Enabling Large-Scale Research on Autism Spectrum Disorders Through Automated Processing of EHR Using Natural Language Understanding

Transforming Kidney Care in the Emergency Department Using Artificial Intelligence-Driven Clinical Decision Support

Description: 

This research will develop and evaluate an artificial intelligence-driven clinical decision support system to detect and manage acute kidney injury in the emergency department.

Principal Investigator: 
Jeremiah S. Hinson
Scott R. Levin
Project Dates: 
September 30, 2020 to July 31, 2021

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.
Principal Investigator: 
Zhou, Li
Project Name: 
Improving Allergy Documentation and Clinical Decision Support in the Electronic Health Record

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: 
Leroy, Gondy
Project Name: 
Enabling Large-Scale Research on Autism Spectrum Disorders Through Automated Processing of EHR Using Natural Language Understanding

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.
Principal Investigator: 
Avidan, Michael
Project Name: 
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

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.
Principal Investigator: 
Avidan, Michael
Project Name: 
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

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: 
Turchin, Alexander
Project Name: 
Identification of Patients with Low Life Expectancy

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.
Principal Investigator: 
Pratap, Jayant
Project Name: 
Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation