The Application of Artificial Intelligence and Machine Learning to Anesthesiology
DOI:
https://doi.org/10.47611/jsrhs.v12i2.4403Keywords:
Artificial Intelligence, Machine Learning, Anesthesiology, Deep Learning, Decision-Making, AlgorithmAbstract
This research paper explores the application of artificial intelligence (AI) and machine learning (ML) in anesthesiology. AI and ML have the potential to improve patient outcomes and enhance clinical decision-making by enabling anesthesiologists to monitor patient vital signs in real-time, predict the likelihood of complications, and optimize drug dosages to minimize side effects and enhance efficacy. The Hypotension Prediction Index algorithm is a compelling example of how AI and ML can be utilized to improve intraoperative patient care. However, there is a need for further research and validation to ensure the safety and efficacy of these technologies in clinical practice. Future advancements in AI and ML techniques are likely to result in more sophisticated and accurate predictive models, decision support tools, and monitoring systems that will ultimately benefit patients undergoing anesthesia. Overall, the application of AI and ML in anesthesiology presents a promising avenue for improving patient care and outcomes.
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Copyright (c) 2023 Srinithya Kothapalli; Dr. Rajagopal Appavu PhD.
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