Evaluation of machine learning models as decision aids for anesthesiologists-Reference-Cited by-同舟云学术

Evaluation of machine learning models as decision aids for anesthesiologists

Published:2022-06-09 Issue:1 Volume:37 Page:155-163
ISSN:1387-1307
Container-title:Journal of Clinical Monitoring and Computing
language:en
Short-container-title:J Clin Monit Comput

Author:

Velagapudi Mihir,Nair Akira A.,Strodtbeck Wyndam,Flynn David N.,Howell Keith,Liberman Justin S.,Strunk Joseph D.,Horibe Mayumi,Harika Ricky,Alamdari Ava,Hembrador Sheena,Kantamneni Sowmya,Nair Bala G.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Anesthesiology and Pain Medicine,Critical Care and Intensive Care Medicine,Health Informatics

Link

https://link.springer.com/content/pdf/10.1007/s10877-022-00872-8.pdf

Reference17 articles.

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2. Hashimoto DA, Witkowski E, Gao L, Meireles O, Rosman G. Artificial intelligence in anesthesiology: current techniques, clinical applications, and limitations. Anesthesiology. 2020;132(2):379–94. https://doi.org/10.1097/aln.0000000000002960.

3. Connor CW. Artificial intelligence and machine learning in anesthesiology. Anesthesiology. 2019;131(6):1346–59. https://doi.org/10.1097/aln.0000000000002694.

4. Lonsdale H, Jalali A, Gálvez JA, Ahumada LM, Simpao AF. Artificial intelligence in anesthesiology: hype, hope, and hurdles. Anesth Analg. 2020;130(5):1111–3. https://doi.org/10.1213/ane.0000000000004751.

5. 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(4):619–22. https://doi.org/10.1097/aln.0000000000002384.

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