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Indian Journal of Anesthesia and Analgesia 11(1):p 49-53, January - March 2024. | DOI: https://doi.org/10.21088/ijaa.2349.8471.11124.9
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Anaesthesia Past, Present and Future
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Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
Indian Journal of Anesthesia and Analgesia 11(1):p 49-53, January - March 2024. | DOI: https://doi.org/10.21088/ijaa.2349.8471.11124.9
How Cite This Article:
Nair A. Anaesthesia past, present and future. Indian J Anesth Analg. 2024;11(1):49-53.Timeline
Received : June 14, 2023
Accepted : August 05, 2023
Published : March 07, 2024
Abstract
Rapid advances in Artificial Intelligence (AI) have led to diagnostic, therapeutic, and intervention based applications in the field of medicine. Today, there is a deep chasm between AI based research articles and their translation to clinical anaesthesia, which needs to be addressed. Machine learning (ML), the most widely applied arm of AI in medicine, confers the ability to analyse large volumes of data, find associations, and predict outcomes with ongoing learning by the computer. It involves algorithm creation, testing and analyses with the ability to perform cognitive functions including association between variables, pattern recognition, and prediction of outcomes. AI supported closed loops have been designed for pharmacological maintenance of anaesthesia and hemodynamic management. Mechanical robots can perform dexterity and skill based tasks such as intubation and regional blocks with precision, whereas clinical decision support systems in crisis situations may augment the role of the clinician. The possibilities are boundless, yet widespread adoption of AI is still far from the ground reality. Patient related “Big Data” collection, validation, transfer, and testing are under ethical scrutiny. For this narrative review, we conducted a PubMed search in 2020-21 and retrieved articles related to AI and anaesthesia. After careful consideration of the content, we prepared the review to highlight the growing importance of AI in anaesthesia. Awareness and understanding of the basics of AI are the first steps to be undertaken by clinicians. In this narrative review, we have discussed salient features of ongoing AI research related to anaesthesia and perioperative care.
References
- 1. Hashimoto DA, Witkowski E, Gao L, Meireles O, Rosman G. Artificial intelligence in anesthesiology: current techniques, clinical applications, and limitations. Anesthesiology. 2020 Feb 1;132(2):379- 94.
- 2. Shimabukuro DW, Barton CW, Feldman MD, Mataraso SJ, Das R: Effect of a machine learningbased severe sepsis prediction algorithm on patient survival and hospital length of stay: A randomised clinical trial. BMJ Open Respir Res 2017; 4:e000234.
- 3. Smistad E, Lovstakken L, Carneiro G, Mateus D, Peter L, Bradley A, Tavares J, Belagiannis V, Papa JP, Nascimento JC, Loog M, Lu Z, Cardoso JS, Cornebise J: Vessel Detection in Ultrasound Images Using Deep Convolutional Neural Networks, Med Image ComputComput Assist Inter, Springer, 2016, pp 30–8.
Data Sharing Statement
There are no additional data available.
Funding
This research received no funding.
Author Contributions
All authors contributed significantly to the work and approve its publication.
Ethics Declaration
This article does not involve any human or animal subjects, and therefore does not require ethics approval.
Acknowledgements
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Conflicts of Interest
The authors report no conflicts of interest in this work.
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Cite this article
Nair A. Anaesthesia past, present and future. Indian J Anesth Analg. 2024;11(1):49-53.
Licence:
Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
| Received | Accepted | Published |
|---|---|---|
| June 14, 2023 | August 05, 2023 | March 07, 2024 |
DOI: https://doi.org/10.21088/ijaa.2349.8471.11124.9
Keywords
Advances in anaesthesiaArtificial intelligenceMachine learningSEDASYSRespirocytesTelemedicineSearch for Similar Articles
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Timeline
| Received | June 14, 2023 |
| Accepted | August 05, 2023 |
| Published | March 07, 2024 |
licence
Attribution-Non-commercial 4.0 International (CC BY-NC 4.0)
This license enables reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
