可解释的人工智能:伦理框架,偏见和对基准的必要性
Rosa Verhoeven1, Wiam Bouisaghouane2, Jan Bf Hulscher1
1Department of Surgery, Division of Pediatric Surgery, University Medical Center Groningen, University of Groningen, The Netherlands.
概括
可解释的人工智能 (XAI) 通过使人工智能 (AI) 的决策可解释,提高了对儿科医疗保健的信任和安全. 解决偏见和道德框架对于为儿童开发公平的AI工具至关重要.
科学领域:
- 儿科手术 儿科手术
- 人工智能的人工智能
- 医学伦理 医学伦理
背景情况:
- 人工智能 (AI) 在儿科医疗保健中的整合提供了更好的诊断和决策.
- 人工智能模型的复杂性引起了人们对儿科患者的信任,透明度和安全的担忧.
- 可解释性AI (XAI) 旨在提高AI驱动的医疗决策的解释性和问责制.
研究的目的:
- 审查XAI在儿科手术中的作用和挑战.
- 强调在儿科护理中对人工智能的伦理框架和标准化基准的关键需求.
- 为未来的研究和实施儿童可信的人工智能解决方案提供建议.
主要方法:
- 在儿科手术中解释性AI (XAI) 应用的文献综述.
- 分析包括偏见,透明度和儿童人工智能的安全性在内的挑战.
- 在儿童医疗保健中实施AI的伦理考虑和要求的综合.
主要成果:
- XAI对于确保人工智能在儿科手术中安全有效地使用至关重要.
- 人工智能算法的偏差对儿科患者护理构成重大风险.
- 标准化的基准和强有力的道德准则是可信的人工智能开发所必需的.
结论:
- 在儿科手术中实施XAI需要仔细考虑道德含义和潜在偏见.
- 未来的研究应该专注于开发针对儿科应用量身定制的透明,公平和安全的AI工具.
- 合作对于在儿科医疗保健中部署人工智能的强大框架至关重要.
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