{"title":"卷积神经网络在肺癌中的应用","authors":"Puja Gupta, S. Garg, Ashwani Garg","doi":"10.2139/ssrn.3562893","DOIUrl":null,"url":null,"abstract":"Lung cancer is the deadliest cancer of the recent decade.75% of the cases are diagnosed in latter stage of cancer, thus the survivalist decreases. With invent of AlexNet in the year 2012 which can train millions of images accurately classified, the role of computer diagnosis increased. This represents a holistic view in reviewing the papers on Lung image database consortium dataset with use of CNN in variant ways to increase sensitivity and accuracy. Small, unvalidated and superficial methods obstruct the usage of CNN.","PeriodicalId":348376,"journal":{"name":"EngRN: Medical Technologies (Topic)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Convolutional Neural Network for Lung Cancer:\",\"authors\":\"Puja Gupta, S. Garg, Ashwani Garg\",\"doi\":\"10.2139/ssrn.3562893\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lung cancer is the deadliest cancer of the recent decade.75% of the cases are diagnosed in latter stage of cancer, thus the survivalist decreases. With invent of AlexNet in the year 2012 which can train millions of images accurately classified, the role of computer diagnosis increased. This represents a holistic view in reviewing the papers on Lung image database consortium dataset with use of CNN in variant ways to increase sensitivity and accuracy. Small, unvalidated and superficial methods obstruct the usage of CNN.\",\"PeriodicalId\":348376,\"journal\":{\"name\":\"EngRN: Medical Technologies (Topic)\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-03-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"EngRN: Medical Technologies (Topic)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3562893\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"EngRN: Medical Technologies (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3562893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Lung cancer is the deadliest cancer of the recent decade.75% of the cases are diagnosed in latter stage of cancer, thus the survivalist decreases. With invent of AlexNet in the year 2012 which can train millions of images accurately classified, the role of computer diagnosis increased. This represents a holistic view in reviewing the papers on Lung image database consortium dataset with use of CNN in variant ways to increase sensitivity and accuracy. Small, unvalidated and superficial methods obstruct the usage of CNN.
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