使用计算机断层扫描进行准确诊断,定量测量和COVID-19肺炎预后的临床应用人工智能系统
Kang Zhang1, Xiaohong Liu2, Jun Shen3
1Faculty of Medicine, Macau University of Science and Technology, Macau, China.
Cell
|May 17, 2020
概括
人工智能系统有助于诊断新型冠状病毒肺炎 (NCP) 和识别高风险患者. 这个人工智能工具分析CT扫描以帮助临床医生,改善COVID-19大流行期间的早期干预和资源分配.
科学领域:
- 医学成像
- 人工智能
- 肺病学
背景情况:
- 由SARS-CoV-2病毒引起的COVID-19经常导致肺炎 (新型冠状病毒肺炎,NCP) 和呼吸衰竭.
- 快速诊断和识别高风险的NCP患者对于及时干预至关重要,但仍然具有挑战性.
- 超负担的医疗保健系统需要有效的诊断工具.
研究的目的:
- 开发和验证使用CT成像诊断NCP的AI系统.
- 为了区分NCP与其他肺炎和正常对照.
- 确定预测NCP严重性和预后的临床标志物.
主要方法:
- 在3777名患者CT扫描的大数据集上训练的AI系统的开发.
- 对NCP的AI系统诊断准确性的验证.
- 人工智能识别标记,临床数据和患者预后之间的相关性分析.
主要成果:
- 人工智能系统准确地诊断出NCP并将其与其他疾病区分开来.
- 通过AI确定了与NCP病变特征相关的显著临床标志物.
- 当与临床数据相结合时,人工智能系统提供了准确的临床预测.
结论:
- 开发的AI系统为快速NCP诊断和风险分层提供了有价值的工具.
- 人工智能辅助的CT扫描分析可以支持放射科医生和临床医生,特别是在健康危机期间.
- 该系统的预后能力可以指导COVID-19患者的早期临床管理和资源分配.
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