Diagnosing the degree of differentiation between types of oral cancer based on extreme deep neural network model and Raman spectroscopy

IF 1.1 4区化学 Q3 SPECTROSCOPY

Spectroscopy Letters Pub Date : 2024-05-17 DOI:10.1080/00387010.2024.2349143

Zishuo Chen, Zengyun Gong, Chenjie Chang, Chen Chen, Xiaoyi Lv, Cheng Chen

引用次数: 0

Abstract

As a highly prevalent and recurrent cancer, detecting the degree of differentiation in oral cancer is crucial. Current methods rely on biopsies in the presence of significant lesions, which are tim...

查看原文本刊更多论文

基于极端深度神经网络模型和拉曼光谱诊断口腔癌类型的分化程度

作为一种高发和复发性癌症，检测口腔癌的分化程度至关重要。目前的方法依赖于在出现明显病变时进行活组织检查，而这需要时间...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Spectroscopy Letters 物理-光谱学

CiteScore

2.90

自引率

5.90%

发文量

审稿时长

1.3 months

期刊介绍： Spectroscopy Letters provides vital coverage of all types of spectroscopy across all the disciplines where they are used—including novel work in fundamental spectroscopy, applications, diagnostics and instrumentation. The audience is intended to be all practicing spectroscopists across all scientific (and some engineering) disciplines, including: physics, chemistry, biology, instrumentation science, and pharmaceutical science.