"Diagnoses in multiple types of cancer based on serum Raman spectroscopy combined with a convolutional neural network: Gastric cancer, colon cancer, rectal cancer, lung cancer"

作者全名："Du, Yu; Hu, Lin; Wu, Guohua; Tang, Yishu; Cai, Xiongwei; Yin, Longfei"

作者地址："[Du, Yu; Wu, Guohua; Yin, Longfei] Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China; [Hu, Lin; Tang, Yishu] Chongqing Med Univ, Affiliated Hosp 1, Dept Lab Med, Chongqing 400016, Peoples R China; [Cai, Xiongwei] Chongqing Med Univ, Chongqing Hlth Ctr Women & Children, Dept Gynecol, Women & Childrens Hosp, Chongqing 400016, Peoples R China"

通信作者："Wu, GH (通讯作者)，Beijing Univ Posts & Telecommun, Sch Elect Engn, Beijing 100876, Peoples R China.; Tang, YS (通讯作者)，Chongqing Med Univ, Affiliated Hosp 1, Dept Lab Med, Chongqing 400016, Peoples R China."

来源：SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY

ESI学科分类：CHEMISTRY

WOS号：WOS:001055071900001

JCR分区：Q1

影响因子：4.3

年份：2023

卷号：298

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：Diagnose; Cancer; Serum; Raman spectroscopy; Convolutional neural network

摘要："Cancer is one of the major diseases that seriously threaten human health. Timely screening is beneficial to the cure of cancer. There are some shortcomings in current diagnosis methods, so it is very important to find a lowcost, fast, and nondestructive cancer screening technology. In this study, we demonstrated that serum Raman spectroscopy combined with a convolutional neural network model can be used for the diagnosis of four types of cancer including gastric cancer, colon cancer, rectal cancer, and lung cancer. Raman spectra database containing four types of cancer and healthy controls was established and a one-dimensional convolutional neural network (1D-CNN) was constructed. The classification accuracy of the Raman spectra combined with the 1D-CNN model was 94.5%. A convolutional neural network (CNN) is regarded as a black box, and the learning mechanism of the model is not clear. Therefore, we tried to visualize the CNN features of each convolutional layer in the diagnosis of rectal cancer. Overall, Raman spectroscopy combined with the CNN model is an effective tool that can be used to distinguish different cancer from healthy controls."

基金机构：National Natural Science Foundation of China (NSFC) [2023- YC-A087]; Innovation and Entrepreneurship Project of Beijing University of Posts and Telecommunications; Beijing Key Laboratory of Work Safety Intelligent Monitoring; [62071059]

基金资助正文："This study is supported by National Natural Science Foundation of China (NSFC) (Grants 62071059) , Innovation and Entrepreneurship Project of Beijing University of Posts and Telecommunications (2023- YC-A087) , and Beijing Key Laboratory of Work Safety Intelligent Monitoring."