以人工智能为基础的算法,通过急性胸部计算机断层扫描检测心脏和肺部疾病:算法开发和验证研究协议
Anne Sophie Overgaard Olesen1, Kristina Miger1, Silas Nyboe Ørting2
1Department of Cardiology, Bispebjerg Hospital, Copenhagen, Denmark.
JMIR research protocols
|September 19, 2025
概括
人工智能 (AI) 算法正在开发中,用于分析胸部CT扫描,以检测心脏衰竭等疾病. 这旨在加快呼吸困难 (呼吸不良) 患者的诊断.
科学领域:
- 医学成像分析 医学成像分析
- 医疗保健中的人工智能
- 诊断工具 诊断工具
背景情况:
- 呼吸障碍是老年人住院的常见原因,往往难以诊断.
- 胸部计算机断层扫描 (CT) 提供了比放射图更好的准确性,但面临着放射科医生的短缺.
- 人工智能可能会自动化CT扫描分析,以帮助诊断.
研究的目的:
- 开发和验证人工智能算法,用于对急性胸部CT扫描进行自动分析.
- 提供立即反肺炎,肺栓塞和心脏衰竭的可能性.
- 专注于开发人工智能用于心脏失补偿检测.
主要方法:
- 使用4672次急性胸部CT扫描 (2016-2021) 的回顾性研究.
- 随机分为培训 (2/3) 和内部验证 (1/3) 套.
- 人工智能开发涉及交叉验证;验证使用放射性报告作为基础真相.
主要成果:
- CT数据提取完成;算法开发正在进行中.
- 对肺堵塞的AI算法开发工作已经完成.
- 计划进行内部和外部验证,结果预计在2026年.
结论:
- 预计来自CT扫描的AI驱动的洞察力将改善临床决策.
- 立即反将使临床医生和呼吸障碍患者受益.
- 有潜力解决多种疾病的老年人诊断挑战.
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