{"title":"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","authors":"Zishuo Chen, Zengyun Gong, Chenjie Chang, Chen Chen, Xiaoyi Lv, Cheng Chen","doi":"10.1080/00387010.2024.2349143","DOIUrl":null,"url":null,"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...","PeriodicalId":21953,"journal":{"name":"Spectroscopy Letters","volume":"50 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnosing the degree of differentiation between types of oral cancer based on extreme deep neural network model and Raman spectroscopy\",\"authors\":\"Zishuo Chen, Zengyun Gong, Chenjie Chang, Chen Chen, Xiaoyi Lv, Cheng Chen\",\"doi\":\"10.1080/00387010.2024.2349143\",\"DOIUrl\":null,\"url\":null,\"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...\",\"PeriodicalId\":21953,\"journal\":{\"name\":\"Spectroscopy Letters\",\"volume\":\"50 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Spectroscopy Letters\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://doi.org/10.1080/00387010.2024.2349143\",\"RegionNum\":4,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"SPECTROSCOPY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Spectroscopy Letters","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1080/00387010.2024.2349143","RegionNum":4,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SPECTROSCOPY","Score":null,"Total":0}
Diagnosing the degree of differentiation between types of oral cancer based on extreme deep neural network model and Raman spectroscopy
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...
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.