心血管疾病预防中的人工智能:它准备好了吗?
Shyon Parsa1, Sulaiman Somani1, Ramzi Dudum2
1Department of Medicine, Stanford University, Stanford, California, USA.
Current atherosclerosis reports
|May 23, 2024
概括
人工智能 (AI) 通过分析临床数据来改善动脉样硬化心血管疾病 (ASCVD) 风险评估和查. 人工智能提供个性化的评估,并增强预防性护理的遵守,为临床整合铺平了道路.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 动脉样性心血管疾病 (ASCVD) 仍然是全球主要的死亡原因.
- 传统的风险评估得分在个性化风险预测方面存在局限性.
- 将先进的数据分析集成到预防性心脏病学中,对于改善患者的治疗结果至关重要.
研究的目的:
- 审查人工智能 (AI) 在提高ASCVD风险评估中的作用.
- 探索AI在机会性选和准则遵守方面的能力.
- 讨论将人工智能纳入预防性心脏病学临床实践的战略.
主要方法:
- 使用人工智能模型分析非结构化临床数据和患者生成的数据.
- 在个性化ASCVD风险预测中评估AI性能.
- 审查AI应用在识别ASCVD风险标志物从各种成像模式的AI应用.
- 评估大型语言模型 (LLM) 管道,以解决护理差距和差异.
主要成果:
- 人工智能模型在与传统得分相比,在个性化的ASCVD风险评估中表现优越.
- 人工智能能够自动检测ASCVD风险标志物,如冠状动脉 (CAC) 来自各种成像来源 (CT,X射线,乳房影像).
- 通过LLM管道,有效地识别和缓解ASCVD预防护理中的差异,并改善患者教育.
结论:
- 人工智能显著提高ASCVD风险评估,机会性查和准则遵守.
- 人工智能应用程序是ASCVD预防和管理的宝贵工具,已准备好临床部署.
- 成功的整合需要对人工智能实施有良好的监管,代的临床途径.
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