人工智能与肺癌查的整合:在公共卫生环境中开发人工智能的考虑因素
James L Mulshine1, Ricardo S Avila2, Mario Silva3
1Department of Internal Medicine, Rush University, Chicago, IL, USA; Center for Healthy Aging, Rush University, 1700 W van Buren St Suite 245, Chicago, IL 60612, USA.
European journal of cancer (Oxford, England : 1990)
|March 16, 2025
概括
肺癌查可以识别早期的肺癌和其他疾病,如肺气和冠状动脉疾病. 开发强大的胸部CT查基础设施对于公共卫生至关重要,整合人工智能用于更好的诊断.
科学领域:
- 放射学和医学成像学 医学成像学
- 公共卫生 公共卫生
- 人工智能在医学中的应用
背景情况:
- 在老年人中,暴露于烟草的肺癌查 (LCS) 揭示了诸如肺气和冠状动脉疾病 (CAD) 等偶然发现.
- 基于这些发现的干预措施,特别是冠状动脉的确立方案存在.
- 越来越多的LCS需要审查选基础设施的发展.
研究的目的:
- 审查开发有效的胸部CT查基础设施的问题.
- 解决先进图像分析的整合,包括人工智能 (AI).
- 为了平衡人工智能工具开发人员的需求与公共卫生要求,以实现公平和可访问的查.
主要方法:
- 审查当前的LCS实践和新兴的诊断创新.
- 分析成像方法要求,以可靠地定量描述肺结节,肺气和冠状动脉疾病.
- 考虑AI在胸部CT查中的作用及其对精度,可重现性和成本的影响.
主要成果:
- 肺结节的成功取决于肺结节 (3-15毫米) 的精确表征.
- 类似的成像质量对于可靠量化肺气和冠状动脉疾病至关重要.
- 人工智能正在显著影响医学成像,包括胸部CT查.
结论:
- 由于技术进步和参与者数量的增加,开发强大的胸部CT查基础设施是及时的.
- 在胸部CT查中整合AI需要仔细考虑,以确保精度,可重复性和成本效益.
- 全球肺部和心脏疾病早期检测和治疗联盟 (AGILE DxRx) 旨在利用先进的计算工具促进公平,高质量,多学科的胸部CT查.
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