Construction of a Machine Learning-Based Risk Scoring Tool for Post-traumatic Acute Hypotension

Author:

Li Tingting,Jia Ruiqi,Li Jing

Publisher

Springer Nature Singapore

Reference18 articles.

1. Moody, G.B., Lehman, L.: Predicting acute hypotensive episodes: the 10th annual PhysioNet/Computers in cardiology challenge. In: Computer in Cardiology, vol. 36.5445351, 541 (2009)

2. A. Janghorbani, A. Arasteh and M. H. Moradi, “Prediction of acute hypotension episodes using Logistic Regression model and Support Vector Machine: A comparative study,” 2011 19th Iranian Conference on Electrical Engineering, Tehran, Iran, 2011, pp. 1–4. Guyton AC. 1996. Text book of physiology. Vol. I. Philadelphia,PA: W.B. Saunders

3. Van Klei, W.A., et al.:Association between intraoperative hypotension and myocardial injury after vascular surgery. In: Survey of anesthesiology (2016)

4. Walsh, M., et al.: Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology 119(3), 507–515 (2013)

5. Kazmers, A., Jacobs, L., Perkins, A.: The impact of complications after vascular surgery in veterans affairs medical centers. J. Surg. Res. 67(1), 62–66 (1997)

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