Avidan, Michael

Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications.

Citation
Xue B, Li D, Lu C, King CR, Wildes T, Avidan MS, Kannampallil T, Abraham J. Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications. JAMA Netw Open. 2021 Mar 1;4(3):e212240. doi: 10.1001/jamanetworkopen.2021.2240. PMID: 33783520; PMCID: PMC8010590.
Principal Investigator
Avidan, Michael
Project Name
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

Study protocol for the Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: a pilot randomized controlled trial in intraoperative telemedicine.

Citation
Gregory S, Murray-Torres TM, Fritz BA, Ben Abdallah A, Helsten DL, Wildes TS, Sharma A, Avidan MS; ACTFAST Study Group. Study protocol for the Anesthesiology Control Tower-Feedback Alerts to Supplement Treatments (ACTFAST-3) trial: a pilot randomized controlled trial in intraoperative telemedicine. F1000Res. 2018 May 22;7:623. doi: 10.12688/f1000research.14897.2. PMID: 30026931.
Principal Investigator
Avidan, Michael
Project Name
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

Anesthesiology Control Tower-Feasibility Assessment to Support Translation (ACTFAST): mixed-methods study of a novel telemedicine-based support system for the operating room.

Citation
Murray-Torres T, Casarella A, Bollini M, Wallace F, Avidan MS, Politi MC. Anesthesiology Control Tower-Feasibility Assessment to Support Translation (ACTFAST): mixed-methods study of a novel telemedicine-based support system for the operating room. JMIR Hum Factors. 2019 Apr 23;6(2):e12155. doi: 10.2196/12155. PMID: 31012859.
Principal Investigator
Avidan, Michael
Project Name
Anesthesiology Control Tower: Feedback Alerts to Supplement Treatment (ACTFAST)

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