Journal of Biosciences and Medicines

Volume 7, Issue 11 (November 2019)

ISSN Print: 2327-5081   ISSN Online: 2327-509X

Google-based Impact Factor: 0.80  Citations  

Future of Artificial Intelligence in Anesthetics and Pain Management

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DOI: 10.4236/jbm.2019.711010    1,145 Downloads   3,824 Views  Citations

ABSTRACT

The potential of the second wave of Artificial Intelligence (AI) to change our lives beyond recognition is both exciting and challenging. AI has been around for over three decades, and this new approach of artificial intelligence, due to enhancements in technology, both software, and hardware, has resulted in the fact that human decision-making is considered inferior and erratic in many fields: none more so than medicine. Machine learning algorithms with access to large data sets can be trained to outperform clinicians in many respects. AI’s effectiveness in accurate diagnosis of various medical conditions and medical image interpretation is well documented. Modern AI technology has the potential to transform medicine to a level never seen before in terms of efficiency and accuracy; but is also potentially highly disruptive, creating insecurity and allowing the transfer of expert domain knowledge to machines. Anesthetics is a complex medical discipline and assuming AI can easily replace experienced and knowledgeable medical practitioners is a very unrealistic expectation. AI can be used in anesthetics to develop, in some respects, more advanced clinical decision support tools based on machine learning. This paper focuses on the complexity of both AI developments, deep learning, neural networks, etc. and opportunities of AI in anesthetics for the future. It will review current advances in AI tools and hardware technologies as well as outlining how these can be used in the field of anesthetics.

Share and Cite:

McGrath, H. , Flanagan, C. , Zeng, L. and Lei, Y. (2019) Future of Artificial Intelligence in Anesthetics and Pain Management. Journal of Biosciences and Medicines, 7, 111-118. doi: 10.4236/jbm.2019.711010.

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