人工智能和抗生素治疗的处方:现在和未来
Daniele Roberto Giacobbe1,2, Cristina Marelli2, Sabrina Guastavino3
1Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy.
Expert review of anti-infective therapy
|August 19, 2024
概括
机器学习 (ML) 为抗生素处方提供了有希望的决策支持,改善了临床结果. 然而,必须解决数据透明度,模型可解释性和伦理框架方面的挑战,以实现广泛采用.
科学领域:
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
- 临床决策支持系统 临床决策支持系统
背景情况:
- 人工智能 (AI) 和机器学习 (ML) 正在医疗保健领域迅速发展.
- 抗生素处方是一个复杂的临床过程,受益于人工智能支持.
- 目前正在探索各种ML技术,以帮助抗生素处方决策.
研究的目的:
- 审查基于ML的临床决策支持系统 (ML-CDSSs) 对抗生素处方的承诺和挑战.
- 探索ML-CDSS对临床结果的潜在影响.
- 确定该领域未来研发的重点领域.
主要方法:
- 进行了叙事审查.
- 在PubMed进行文献搜索,截至2024年4月.
- 对抗生素处方中ML应用现有研究的分析.
主要成果:
- ML-CDSS显示出可能对抗生素处方的临床结果产生有利影响.
- 研究表明,ML-CDSS能够改善相关的临床结果.
- 仍然存在重大挑战,包括数据透明度,模型可解释性和法律/道德框架.
结论:
- 在优化抗生素处方方面,ML-CDSS有很大的前景.
- 解决透明度,可解释性和伦理方面的挑战对于成功实施至关重要.
- 需要进一步的研究,以充分利用ML在抗生素管理中的潜力.
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