Free
Infographics in Anesthesiology  |   October 2018
Machine Learning for Anesthesiologists: A Primer
Author Notes
  • Vanderbilt University Medical Center
  • Brigham and Women’s Health Care/Harvard Medical School
  • Illustration by Annemarie Johnson, Vivo Visuals.
    Illustration by Annemarie Johnson, Vivo Visuals.×
  • Address correspondence to Dr. Wanderer: jonathan.p.wanderer@vanderbilt.edu.
Article Information
Infographics in Anesthesiology
Infographics in Anesthesiology   |   October 2018
Machine Learning for Anesthesiologists: A Primer
Anesthesiology 10 2018, Vol.129, A29. doi:10.1097/ALN.0000000000002444
Anesthesiology 10 2018, Vol.129, A29. doi:10.1097/ALN.0000000000002444
Complex Information for Anesthesiologists Presented Quickly and Clearly
Intraop, intraoperative; preop, preoperative.
Infographic created by Jonathan P. Wanderer, Vanderbilt University Medical Center, and James P. Rathmell, Brigham and Women’s Health Care/Harvard Medical School. Illustration by Annemarie Johnson, Vivo Visuals. Address correspondence to Dr. Wanderer: jonathan.p.wanderer@vanderbilt.edu.
Mathis, MR, Kheterpal, S, Najarian, K Artificial intelligence for anesthesia: What the practicing clinician needs to know: More than black magic for the art of the dark. Anesthesiology 2018; 129:619–22 [PubMed]
Hatib, F, Jian, Z, Buddi, S, Lee, C, Settels, J, Sibert, K, Rinehart, J, Cannesson, M Machine-learning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis. Anesthesiology 2018; 129:663–74 [PubMed]
Lee, CK, Hofer, I, Gabel, E, Baldi, P, Cannesson, M Development and validation of a deep neural network model for prediction of postoperative in-hospital mortality. Anesthesiology 2018; 129:649–62 [PubMed]
Kendale, S, Kulkarni, P, Rosenberg, AD, Wang, J Supervised machine learning predictive analytics for prediction of postinduction hypotension. Anesthesiology 2018; 129:675–88 [PubMed]