人工智能和机器学习在麻醉学中的应用

IF 0.9 Q3 EDUCATION & EDUCATIONAL RESEARCH Journal of Student Affairs Research and Practice Pub Date : 2023-05-31 DOI:10.47611/jsrhs.v12i2.4403
Srinithya Kothapalli, Rajagopal Appavu
{"title":"人工智能和机器学习在麻醉学中的应用","authors":"Srinithya Kothapalli, Rajagopal Appavu","doi":"10.47611/jsrhs.v12i2.4403","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":46753,"journal":{"name":"Journal of Student Affairs Research and Practice","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Application of Artificial Intelligence and Machine Learning to Anesthesiology\",\"authors\":\"Srinithya Kothapalli, Rajagopal Appavu\",\"doi\":\"10.47611/jsrhs.v12i2.4403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":46753,\"journal\":{\"name\":\"Journal of Student Affairs Research and Practice\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Student Affairs Research and Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47611/jsrhs.v12i2.4403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Student Affairs Research and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47611/jsrhs.v12i2.4403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
引用次数: 0

摘要

本文探讨了人工智能(AI)和机器学习(ML)在麻醉学中的应用。人工智能和机器学习有可能改善患者的治疗结果,增强临床决策,使麻醉师能够实时监测患者的生命体征,预测并发症的可能性,并优化药物剂量以减少副作用并提高疗效。低血压预测指数算法是人工智能和机器学习如何用于改善术中患者护理的一个引人注目的例子。然而,还需要进一步的研究和验证,以确保这些技术在临床实践中的安全性和有效性。人工智能和机器学习技术的未来发展可能会产生更复杂、更准确的预测模型、决策支持工具和监测系统,最终使麻醉患者受益。总的来说,人工智能和机器学习在麻醉学中的应用为改善患者护理和结果提供了一条有前途的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
The Application of Artificial Intelligence and Machine Learning to Anesthesiology
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Student Affairs Research and Practice
Journal of Student Affairs Research and Practice EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
2.40
自引率
9.10%
发文量
50
期刊介绍: The vision of the Journal of Student Affairs Research and Practice (JSARP) is to publish the most rigorous, relevant, and well-respected research and practice making a difference in student affairs practice. JSARP especially encourages manuscripts that are unconventional in nature and that engage in methodological and epistemological extensions that transcend the boundaries of traditional research inquiries.
期刊最新文献
How White Undergraduates Experience and Make Meaning of Parental Messages about Race The Overlooked Influence of Advising and Supporting Upon Leadership in Student Affairs Delivering on the Promise of High-Impact Practices: Research and Models for Achieving Equity, Fidelity, Impact, and Scale LGBTQ Leadership in Higher Education How Sorority and Fraternity Life Professionals Validate Culturally Based Sororities and Fraternities
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1