大胆:血液气体和氧计相关数据集
João Matos1,2,3,4, Tristan Struja5, Jack Gallifant6,7
1Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA. jcmatos@mit.edu.
Scientific data
|May 24, 2024
概括
BOLD数据集解决了脉冲氧计准确度的种族差异. 这一新数据集旨在通过开发脉冲氧计的脱离算法来改善公平的医疗保健.
科学领域:
- 生物医学工程 生物医学工程
- 医疗信息学 医疗信息学
- 临床研究 临床研究
背景情况:
- 脉冲氧计提供非侵入性的外围动脉氧和度 (SpO2) 测量.
- 动脉血液气体 (SaO2) 测量是氧和度的黄金标准.
- 现有的脉冲氧计技术表现出已知的种族和民族性能差异.
研究的目的:
- 引入BOLD数据集,旨在突出并解决脉冲氧计准确度中的偏差.
- 专注于脉冲氧计不准确性对肤色较暗的个体的不成比例影响.
- 为了促进为更公平的医疗保健开发 debiasing 算法.
主要方法:
- 协调了美国重症监护病房的三个电子健康记录数据库 (MIMIC-III,MIMIC-IV,eICU-CRD).
- 收集了配对的SpO2和SaO2测量,在5分钟的窗口内时间调整.
- 包括社会人口统计数据和其他参数,以提供全面的患者代表.
主要成果:
- BOLD数据集包括49,099个对对测量 (SpO2/SaO2) 在70-100%的氧和度之间.
- 少数种族和少数民族群体约占数据集的25%.
- BOLD数据集的代码库是公开的.
结论:
- BOLD数据集是了解和减轻脉冲氧计偏差的宝贵资源.
- 数据集的组成,少数群体的显著代表性,对于偏见研究至关重要.
- 利用BOLD可以为所有患者开发更好的,公平的脉冲氧计解决方案.
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