走向值得信赖的医疗人工智能的道路:可解释性的演变作用
Francesca Aurora Sacchi1, Fidelia Cascini2, Noemi Conditi3
1Italian Society for Artificial Intelligence in Medicine (SIIAM - Società Italiana Intelligenza Artificiale in Medicina), Rome, Italy - Public Health Department, Monroe University, New York.
Recenti progressi in medicina
|October 2, 2025
概括
人工智能 (AI) 在医学中至关重要,但往往缺乏可解释性. 这一观点考察了人工智能可解释性的演变,从伦理问题变成法律要求,影响信任和准确性.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 临床决策支持 临床决策支持
背景情况:
- 人工智能 (AI) 在医学中提供了广泛的应用,包括预防,诊断,治疗和远程护理.
- 当前人工智能系统的一个重大挑战是它们的解释能力有限,这阻碍了对它们的决策过程的理解.
- 这种缺乏透明度在临床环境中给开发人员和最终用户带来了问题.
研究的目的:
- 探索AI可解释性在医学领域的关键重要性.
- 追踪人工智能可解释性从伦理考虑到法律要求的转变.
- 分析AI可解释性,系统可靠性和技术方法之间的关系.
主要方法:
- 文献综述和概念分析.
- 检查AI可解释性要求的演变.
- 讨论实现AI可解释性的技术方法.
主要成果:
- 人工智能可解释性已经从伦理问题演变为医学中的法律要求.
- 可解释性与医疗人工智能系统的可信度密切相关.
- 对AI可解释性的技术方法往往与实现最大精度的权衡.
结论:
- 确保AI可解释性对于安全有效地融入临床实践至关重要.
- 对医疗人工智能的信任取决于透明和可理解的决策过程.
- 在开发可靠的医疗人工智能方面,平衡可解释性和准确性是关键的挑战.
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