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Research Activities in Clinical Informatics

Share Last Updated: September 11, 2018


Overview: Emory’s clinical informatics faculty are building the next generation of algorithms and data infrastructure to impact clinical care at Emory and beyond. In collaboration with Emory’s clinical departments, BMI is developing streaming infrastructure for the Intensive Care Unit to enable machine-learning based interventions in complex problems like sepsis prediction and medication dosing where real-time decision-making drives outcomes. Emory’s work with the EMR system are focused on developing improving the accuracy of data capture using novel signal processing, and developing algorithms to improve healthcare quality, cost-effectiveness, and patient outcomes. The strength of Emory’s clinical departments and BMI faculty provide excellent cross-training opportunities for students interested in clinical informatics.

Active Projects: Eureka Clinical; Deep Learning for ICU predictions ; 

Faculty: Gari Clifford; Shamim Nemati;  Andrew Post

Selected Publications:

  •  Nemati, Holder A, Razmi F, Stanley MD, Clifford GD, Buchman TG. An interpretable machine learning model for accurate prediction of sepsis in the ICU. Crit Care Med. 2018 Apr;46(4):547-553 103
  • Shashikumar SP, Stanley MD, Sadiq I, Li Q, Holder A, Clifford GD, Nemati S. Early sepsis detection in critical care patients using multiscale blood pressure and heart rate dynamics. J Electrocardiol. 2017 Nov - Dec;50(6):739-743
  • Shashikumar SP, Li Q, Clifford GD, Nemati S. Multiscale network representation of physiological time series for early prediction of sepsis. Physiol Meas. 2017 Nov 30;38(12):2235-2248
  • Johnson A EW, Ghassemi MM, Nemati S, Niehaus KE, Clifton DA, Clifford GD. Machine learning and decision support in critical care. Proc IEEE Inst ElectrElectron Eng. 2016 Feb;104(2):444-466
  •  Li Q, Rajagopalan C, Clifford GD. Ventricular fibrillation and tachycardia classification using a machine learning approach. IEEE Trans Biomed Eng.2014 Jun;61(6):1607-13 41
  • Johnson A EW, Kramer AA, Clifford GD. A new severity of illness scale using a subset of APACHE data elements shows comparable predictive accuracy. Critical Care Medicine Volume 41 Issue 7 2013

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