健康上的不平等,偏见和人工智能
Hanzhou Li1, John T Moon1, Vishal Shankar2
1Department of Radiology, Emory University, Atlanta, GA.
Techniques in vascular and interventional radiology
|November 3, 2024
概括
人工智能 (AI) 可以帮助减少肌肉骨 (MSK) 疼痛管理方面的差异. 人工智能能识别不平等和偏见,导致更公平的护理和更好的慢性疼痛患者结果.
科学领域:
- 医学成像和干预性放射学
- 健康公平和人工智能 人工智能
背景情况:
- 肌肉骨 (MSK) 疼痛是一个全球性的健康问题,通常是慢性且难以有效管理.
- 在MSK疼痛管理中存在差异,受提供者偏见和患者人口统计学的影响,导致结果不一致.
- 干预放射学 (IR) 为MSK疼痛提供了最少的侵入性解决方案,但由于系统因素,可能未得到充分利用.
研究的目的:
- 探索人工智能 (AI) 在解决MSK疼痛管理中的不平等问题方面的潜力.
- 研究人工智能如何识别和减轻提供者偏见,并提高疼痛护理方面的文化能力.
- 通过人工智能分析电子医疗记录,加强疼痛评估和IR程序的患者识别.
主要方法:
- 人工智能算法分析大型数据集,以确定MSK疼痛管理中的差异.
- 建议使用人工智能工具来识别隐含的偏见,并提高医疗保健提供者之间的文化能力.
- 人工智能促进了多式联络数据分析,以提高疼痛评估和IR程序的患者分层.
主要成果:
- 人工智能可以识别受患者和提供者因素影响的疼痛管理差异.
- 人工智能有可能提高文化能力并减轻提供者的偏见.
- 人工智能可以识别那些可能受益于干预性放射学 (IR) 疼痛手术的患者.
结论:
- 人工智能提供了一种有希望的方法来缓解偏见,并确保更公平的MSK疼痛管理.
- 利用人工智能可以更好地识别符合IR疼痛干预措施的患者.
- 人工智能可以有助于改善治疗慢性MSK疼痛的整体患者结果.
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