人工智能和MRI在鼻腔瘤的歧视:我们站在哪里?
Giacomo Gravante1,2, Alberto Daniele Arosio3, Nico Curti4
1Division of Otorhinolaryngology, Department of Biotechnology and Life Sciences, University of Insubria, Ospedale di Circolo, Varese, Italy. giacomo.gravante1@gmail.com.
概括
人工智能 (AI) 和MRI中的放射学可以准确区分鼻瘤,改善活检前的诊断. 将人工智能与临床数据结合起来可以提高性能,为更好的治疗规划铺平道路.
科学领域:
- 放射学 放射学是一门学科.
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 人工智能 (AI) 在磁共振成像 (MRI) 的放射性分析中显示出有前途的潜力,用于鼻瘤歧视.
- 人工智能可以增强诊断怀疑超出视觉评估,可能加快诊断和治疗规划.
研究的目的:
- 评估AI在基于MRI的鼻瘤歧视中的当前进展和准确性.
主要方法:
- 按照PRISMA指南进行了一次系统的文献审查.
- 包括使用机器学习在MRI上用于鼻瘤的研究.
- 收集了MRI协议,特征提取和分类器的数据;使用精度和AUC来评估性能.
主要成果:
- 包括14项研究 (2017年5月至2024年8月),按所研究的瘤类型分类.
- 所有研究都报告了曲线下面积 (AUC) >0.800,AUC>0.89和精度>0.81,当临床放射学变量被整合时.
- 使用联合常规MRI序列 (T1加权,对比T1加权,T2加权) 实现了最佳的歧视.
结论:
- 在MRI分析中,人工智能和放射学对鼻瘤歧视有显著的前景.
- 整合临床和放射学数据可以提高AI模型的性能.
- 未来的研究应该集中在更大的队列和多样化的AI方法上,以提高诊断准确性和临床实用性.
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