TY - CHAP
T1 - Artificial Intelligence and Predictive Analytics
AU - de Keijzer, Ilonka N.
AU - Vistisen, Simon T.
AU - Thomas, W. L.Scheeren
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2021. All rights reserved.
PY - 2021
Y1 - 2021
N2 - Artificial intelligence (AI) and predictive analytics—a subset of AI techniques—are increasingly used in medicine, and the field of hemodynamic monitoring is no exception. These techniques are used to predict adverse hemodynamic events such as hypotension or tachycardia before they actually occur. In the development of predictive models, steps have to be taken from collection of monitoring data to feature extraction and feature evaluation. Finally, the best model should be selected and the predictive performance evaluated. Predictive models show promising results, yet only few are currently used in clinical practice.
AB - Artificial intelligence (AI) and predictive analytics—a subset of AI techniques—are increasingly used in medicine, and the field of hemodynamic monitoring is no exception. These techniques are used to predict adverse hemodynamic events such as hypotension or tachycardia before they actually occur. In the development of predictive models, steps have to be taken from collection of monitoring data to feature extraction and feature evaluation. Finally, the best model should be selected and the predictive performance evaluated. Predictive models show promising results, yet only few are currently used in clinical practice.
KW - Artificial intelligence
KW - Hemodynamic monitoring
KW - Hypotension
KW - Machine learning
KW - Predictive analytics
KW - Tachycardia
UR - http://www.scopus.com/inward/record.url?scp=85160150737&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-71752-0_29
DO - 10.1007/978-3-030-71752-0_29
M3 - Chapter
AN - SCOPUS:85160150737
SN - 9783030717513
SP - 287
EP - 293
BT - Advanced Hemodynamic Monitoring
PB - Springer International Publishing AG
ER -