TY - GEN
T1 - Perioperative Anesthesia Data
T2 - 4th IEEE International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024
AU - Liu, Xiaoxiao
AU - McGrath, Sean
AU - Flanagan, Colin
AU - Lei, Yiming
AU - Zeng, Liaoyuan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - A comprehensive understanding of physiological data is essential for anesthesiologists to monitor and maintain the health of surgical patients. Understanding anesthetic signals is essential to improve over the past ten decades to comprehend a variety of diseases, ensure the safety of patients, and accelerate their recovery. We identified and summarized four themes of artificial intelligence (AI) research in anesthesia: applications of AI in anesthesiology, signals monitored in different anesthesia stages, commonly monitored signs, and data standardization. The effect of various AI technologies on data analysis was studied, and the types, functions, sensors, characteristics, and intelligent analysis of physiological signals monitored during anesthesia are presented in this article. AI influences anesthesia practices in many ways, including preoperative data evaluation, anesthetic depth monitoring, and postoperative event prediction.
AB - A comprehensive understanding of physiological data is essential for anesthesiologists to monitor and maintain the health of surgical patients. Understanding anesthetic signals is essential to improve over the past ten decades to comprehend a variety of diseases, ensure the safety of patients, and accelerate their recovery. We identified and summarized four themes of artificial intelligence (AI) research in anesthesia: applications of AI in anesthesiology, signals monitored in different anesthesia stages, commonly monitored signs, and data standardization. The effect of various AI technologies on data analysis was studied, and the types, functions, sensors, characteristics, and intelligent analysis of physiological signals monitored during anesthesia are presented in this article. AI influences anesthesia practices in many ways, including preoperative data evaluation, anesthetic depth monitoring, and postoperative event prediction.
KW - anesthesia
KW - artificial intelligence
KW - electroencephalogram
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85201199251&partnerID=8YFLogxK
U2 - 10.1109/ICEIB61477.2024.10602554
DO - 10.1109/ICEIB61477.2024.10602554
M3 - Conference contribution
AN - SCOPUS:85201199251
T3 - 2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024
SP - 746
EP - 751
BT - 2024 IEEE 4th International Conference on Electronic Communications, Internet of Things and Big Data, ICEIB 2024
A2 - Meen, Teen-Hang
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 April 2024 through 21 April 2024
ER -