{"title":"利用深度学习准确检测组织病理学图像中的乳腺癌","authors":"Dhanikonda Ratna Bhavani","doi":"10.22214/ijraset.2024.63736","DOIUrl":null,"url":null,"abstract":"Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.","PeriodicalId":13718,"journal":{"name":"International Journal for Research in Applied Science and Engineering Technology","volume":"18 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Harnessing Deep Learning for Accurate Detection of Breast Cancer in Histopathological Imagery\",\"authors\":\"Dhanikonda Ratna Bhavani\",\"doi\":\"10.22214/ijraset.2024.63736\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.\",\"PeriodicalId\":13718,\"journal\":{\"name\":\"International Journal for Research in Applied Science and Engineering Technology\",\"volume\":\"18 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal for Research in Applied Science and Engineering Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22214/ijraset.2024.63736\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal for Research in Applied Science and Engineering Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22214/ijraset.2024.63736","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
摘要:乳腺癌是继皮肤癌之后妇女中最常见的癌症,是死亡率上升的重要原因。乳房 X 光筛查是检测乳腺癌相关肿块和异常的有效方法。数字乳房 X 光检查尤其适用于无症状妇女的早期癌症检测,以及有肿块或乳头溢液等症状妇女的癌症诊断,从而降低死亡率并提高存活率。临床医生经常面临时间限制,由于没有足够的时间彻底检查病人的病史,可能导致医疗失误和错误诊断。
Harnessing Deep Learning for Accurate Detection of Breast Cancer in Histopathological Imagery
Abstract: Breast cancer, the most common cancer among women after skin cancer, significantly contributes to the rising mortality rate. Screening mammography is an effective method for detecting masses and abnormalities related to breast cancer. Digital mammograms are especially useful for early cancer detection in asymptomatic women and diagnosing cancer in women with symptoms such as lumps or nipple discharge, thereby reducing mortality and increasing survival rates. Clinicians often face time constraints that can lead to medical errors and incorrect diagnoses due to insufficient time to review patient history thoroughly.