预测胸部X射线图中的 natriuretic 的升高:新兴的人工智能利用差距
Eisuke Kagawa1, Masaya Kato1, Noboru Oda1
1Department of Cardiology, Hiroshima City Asa Hospital, 1-2-1, Kameyamaminami, Asakita-ku, Hiroshima 7310293, Japan.
European heart journal. Imaging methods and practice
|October 15, 2024
概括
一个人工智能 (AI) 模型从胸部X射线中准确地预测大脑 natriuretic (BNP) 水平的升高. 人工智能协助显著提高了医疗保健专业人员的诊断准确性,特别是对于早期职业生涯的从业人员.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 预测生物标志物的预测
背景情况:
- 大脑中尿素 (BNP) 水平升高是诊断心力衰竭的关键指标.
- 预测BNP水平通常需要进行血液检测,这可能会推迟诊断.
- 胸部放射学是一种常见的成像方式,可能包含预测信息.
研究的目的:
- 评估AI模型使用胸部放射图预测BNP水平升高的能力.
- 评估人工智能协助对医疗保健专业人员诊断绩效的影响.
主要方法:
- 开发两种整体AI模型,通过胸部X射线预测BNP水平 (≥200 pg/mL和≥100 pg/mL).
- 使用来自另一个医院的数据对AI模型进行外部验证.
- 在35名医疗保健专业人员中,使用和不使用人工智能的诊断准确度的比较.
主要成果:
- 人工智能模型表现出高性能,精度为0.855,AUC为0.929.
- 人工智能辅助显著提高了整体诊断准确度,从0.708到0.829 (P < 0.001).
- 人工智能协助显著提高了早期职业生涯专业人员的表现,超过了经验丰富的临床医生.
结论:
- 人工智能模型可以有效地从胸部放射图中预测BNP水平升高.
- 人工智能工具显示出在临床实践中增强人类诊断能力的巨大潜力.
- 解决新的AI工具的整合差距对于实现它们的全部临床益处至关重要.
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