Article citationsMore>>

Liu, N., Chazot, T., Genty, A., Landais, A., Restoux, A., McGee, K., Laloë, P.-A., Trillat, B., Barvais, L. and Fischler, M. (2006) Titration of Propofol for Anesthetic Induction and Maintenance Guided by the Bispectral Index: Closed-Loop versus Manual Control: A Prospective, Randomized, Multicenter Study. The Journal of the American Society of Anesthesiologists, 104, 686-695.
https://doi.org/10.1097/00000542-200604000-00012

has been cited by the following article:

• TITLE: Artificial Intelligence-Supported Systems in Anesthesiology and Its Standpoint to Date—A Review

  AUTHORS: Fiona M. P. Pham

  KEYWORDS: Artificial Intelligence, Anesthesiology, Machine Learning, Pharmacological Robot, Mechanical Robot, ChatGPT

  JOURNAL NAME: Open Journal of Anesthesiology, Vol.13 No.7, July 14, 2023

  ABSTRACT: Artificial intelligence (AI) is the technique that enables computers to solve problems and perform tasks that traditionally require human intelligence. The availability of large amounts of medical data from electronic medical records and powerful modern microcomputers enables the development of AI in medicine. AI has proven its applicability in many different medical areas, such as drug discovery, diagnostic radiology and pathology, as well as interventional applications in cardiology and surgery. However, until today, AI is scarcely used in the clinical practice of anesthesiology. Although there has been a significant body of research published on AI applications for anesthesiology in the literature, the number of developed robot systems for commercial use or those ready for clinical trials remains limited. The limitations of AI systems are identified and discussed, which include incorrect medical data formatting, individual patient variability, the lack of ability of current AI systems, anesthesiologist inexperience in AI usage, system unreliability, unexplainable AI conclusions and strict regulations. In order to ensure anesthesiologists’ trust in AI systems and improve their implementation in daily practice, strict quality control of the systems and algorithms should be undertaken. Further, anesthesiology personnel should play an integral role in the development of AI systems before we are able to see more AI integration in clinical anesthesiology.