心血管保健创新通过电子健康记录中的数据驱动发现
Lovedeep Singh Dhingra1, Miles Shen2, Anjali Mangla3
1Section of Cardiovascular Medicine, Department of Internal Medicine.
The American journal of cardiology
|July 27, 2023
概括
电子健康记录 (EHR) 为心血管研究提供了有价值的数据. 自然语言处理和联合学习方面的创新,从非结构化的EHR数据中获取洞察力,改善患者的治疗结果.
科学领域:
- 生物医学信息学 生物医学信息学
- 心血管研究研究心血管研究
- 健康 数据科学 数据科学
背景情况:
- 电子健康记录 (EHR) 是患者信息的丰富数据来源.
- 结构化和非结构化的EHR数据可以定义疾病表型和护理特征.
- 目前,非结构化EHR数据,包括临床叙述和报告,在研究中未得到充分利用.
研究的目的:
- 审查利用EHR数据在心血管研究中的挑战和解决方案.
- 突出自然语言处理 (NLP) 和计算机视觉方面的创新,以获取EHR数据.
- 讨论大型,多中心EHR研究的联合学习方法.
主要方法:
- 审查关于在研究中使用EHR数据的现有文献.
- 讨论挑战:保密性,准确性,完整性和异质性.
- 探索技术进步:NLP,计算机视觉和联合学习.
主要成果:
- 结构化EHR数据很容易提取,但非结构化数据具有重要的未开发潜力.
- 随着NLP和计算机视觉的进步,人们可以从非结构化的EHR数据中获得洞察力.
- 联合学习与共同的数据模型有助于大规模的多中心研究.
结论:
- 应对EHR数据挑战需要方法上的创新和最佳实践.
- 技术和研究方法的进步使得创新的患者护理和结果优化成为可能.
- 利用结构化和非结构化EHR数据对于推进心血管研究至关重要.
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