基于图像的口腔科学多主题分析:最近的进展和前景
Yizhuo Chen1, Pengxi Du1, Yinyin Zhang1
1Department of Stomatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.
Journal of dentistry
|October 20, 2024
概括
深度学习增强的多omics分析,包括放射学和病理学,改善了口腔疾病的诊断. 这种方法比传统方法提供了更多的代表性特征,帮助临床医生进行诊断和治疗.
科学领域:
- 口腔和牙面部医学是口腔和牙面部医学.
- 牙科科学 牙科科学
- 医学成像医学成像
背景情况:
- 口腔疾病的诊断依赖于医学成像.
- 深度学习可以从多omics数据中提取优越的特性.
- 传统方法在特征提取方面存在局限性.
研究的目的:
- 审查口腔科学中基于图像的多omics分析的应用和进展.
- 突出提高传统口腔疾病诊断方法的潜力.
- 讨论放射学,病理学和基于照片的奥米克分析.
主要方法:
- 在PubMed,科学网络和谷歌学者系统的文献搜索.
- 综合检查和总结基于图像的多态学方面的进展.
- 专注于口腔和面医学应用.
主要成果:
- 概括了基于图像的口腔科学多omics最近的进展.
- 包括放射学,病理学和基于照片的电子学.
- 确定挑战和未来的前景.
结论:
- 基于图像的多omics分析显示了牙科的潜力.
- 将omics与成像相结合,可以提高诊断的准确性和效率.
- 帮助临床医生进行诊断,治疗,资源管理和知识传播.
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