低剂量计算机断层扫描胸部查中的人工智能:过去,现在和未来
Rowena Yip1, Artit Jirapatnakul1, Ricardo Avila2
1Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York.
Journal of thoracic imaging
|September 30, 2025
概括
与低剂量计算机断层扫描 (LDCT) 集成的人工智能 (AI) 增强了肺癌查,用于早期检测多种疾病. 这种方法承诺通过可扩展的,人工智能驱动的预防性护理改善人口健康.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 预防医学 预防医学
背景情况:
- 低剂量计算机断层扫描 (LDCT) 是为肺癌查而建立的.
- 国际早期肺癌行动计划 (I-ELCAP) 拥有超过30年的研究和实施经验.
- 将人工智能与LDCT集成为更广泛的疾病检测提供了潜力.
研究的目的:
- 审查人工智能的开发和临床整合,用于LDCT扫描解释.
- 突出AI在结节检测,肺气量化和心血管风险评估中的作用.
- 讨论人工智能在现实世界选中的实施挑战和解决方案.
主要方法:
- 对人工智能辅助的LDCT解释的历史里程碑的审查.
- 开源IELCAP-AIRS系统和ScreeningPLUS基础设施的描述.
- 讨论用于结节管理和疾病量化的人工智能算法.
主要成果:
- 人工智能算法展示了从LDCT扫描中早期检测多种疾病的潜力.
- 人工智能可以协助肺结节的检测,肺的量化和心血管风险评估.
- 人工智能工具可以减少放射科医生的工作量,并提前进行精确查.
结论:
- 人工智能驱动的LDCT查可以改变多种疾病的早期检测.
- 可扩展的人工智能解决方案对于改善人口健康和预防保健至关重要.
- 合作,标准化和大型数据集对于在选中推进人工智能至关重要.
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