使用基于ML的技术对肺癌对心血管疾病的影响的协同分析
IEEE journal of biomedical and health informatics
|February 13, 2024
概括
肺癌显著增加了心血管疾病 (CVD) 的风险. 一个新的系统使用肺CT扫描来准确检测肺癌 (98.28%) 和心血管疾病预测 (91.62%),帮助早期干预.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 心脏病学 心脏病学
背景情况:
- 癌症患者患心血管疾病 (CVD) 的风险较高.
- 特别是肺癌与心血管疾病易感性增加密切相关.
- 现有的诊断方法可能无法完全捕捉到肺癌和心血管疾病之间的复杂联系.
研究的目的:
- 使用肺部计算机断层扫描 (CT) 图像开发肺癌检测和心血管疾病预测 (LCDP) 系统.
- 为了研究肺癌和心血管疾病的相互依赖.
- 为了提高两个条件的诊断准确度.
主要方法:
- 肺癌检测采用转移学习 (TL) 与AdaDenseNet和Prox-SMOTE,以提高分类准确度.
- 心血管疾病的预测涉及使用VGG-16模型的特征提取.
- 支持矢量机 (SVM) 分类器被用于CVD预测.
主要成果:
- 在肺癌检测方面,LCDP系统实现了98.28%的高精度.
- 该系统在心血管疾病预测方面表现出了91.62%的显著准确性.
- 评估证实了肺癌对心血管疾病发展的重大影响和相互依赖.
结论:
- 拟议的LCDP系统有效地整合了CT扫描的肺癌检测和心血管疾病预测.
- 这些发现凸显了监测肺癌患者心血管疾病的关键需求.
- 这种人工智能驱动的方法为早期诊断和风险评估提供了有前途的工具.
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