在肺结节风险评估中对人工智能的审查
IEEE reviews in biomedical engineering
|March 3, 2025
概括
人工智能 (AI) 有助于评估超出恶性瘤的肺结节风险,评估亚型,转移和进展. 未来的人工智能开发的目标是提高肺癌诊断的临床解释性和通用性.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 肺癌是全球癌症死亡的主要原因之一.
- 准确的肺结节风险评估对于及时治疗和改善患者结果至关重要.
- 目前对肺结节的AI研究主要集中在恶性瘤分类上,对其他风险因素的探索有限.
研究的目的:
- 在肺结节风险评估中全面审查人工智能 (AI) 应用.
- 涵盖AI在恶性瘤诊断,病理亚型评估,转移风险,受体表达识别和疾病进展中的作用.
- 讨论共同的数据库和人工智能技术,强调它们的优点和局限性.
主要方法:
- 在肺结节风险评估中对人工智能应用的系统文献综述.
- 分析常见的公共数据库和最先进的人工智能技术.
- 识别和讨论好处和挑战,包括数据稀缺性,概括性和可解释性.
主要成果:
- 人工智能在各种肺结节风险评估中显示出潜力,包括恶性瘤,亚型,转移,受体表达和进展.
- 详细介绍了常用的公共数据库和先进的AI方法.
- 确定了数据稀缺性,模型通用性和可解释性等关键挑战.
结论:
- 人工智能为除恶性瘤之外的全面肺结节风险评估提供了一个有希望的途径.
- 解决数据稀缺性,概括性和解释性方面的挑战对于临床整合至关重要.
- 未来的研究应该专注于提高AI的解释性和通用性,以改善肺癌管理中的临床工作流程.
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