{"title":"基于机器学习的乳腺癌检测研究","authors":"Sunpreet Kour, Rakesh Kumar, Meenu Gupta","doi":"10.1109/APSIT52773.2021.9641284","DOIUrl":null,"url":null,"abstract":"Breast cancer is one of the woman's most prominent cancer and most malignant of all cancers. It is the world's largest autopsy of cancer deaths for females and happens in about 3 from 10 people. This article includes numerous machine learning methods and data mining strategies to assess the early detection of breast cancer. Machine learning is used in clinical applications such as identification of cancer cells. The cancerous cells are categorized as Benign and Malignant. This paper analyzes the quality of numerous unsupervised, supervised and other methods for the integrity and prediction for breast cancer. This research could provide various methodologies to better understand early cancer detection. Early detection for breast cancer can be a potential benefit in the management of this condition, not only does early treatment make it possible to heal it, but it also prevent its recurrence.","PeriodicalId":436488,"journal":{"name":"2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Study on detection of breast cancer using Machine Learning\",\"authors\":\"Sunpreet Kour, Rakesh Kumar, Meenu Gupta\",\"doi\":\"10.1109/APSIT52773.2021.9641284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Breast cancer is one of the woman's most prominent cancer and most malignant of all cancers. It is the world's largest autopsy of cancer deaths for females and happens in about 3 from 10 people. This article includes numerous machine learning methods and data mining strategies to assess the early detection of breast cancer. Machine learning is used in clinical applications such as identification of cancer cells. The cancerous cells are categorized as Benign and Malignant. This paper analyzes the quality of numerous unsupervised, supervised and other methods for the integrity and prediction for breast cancer. This research could provide various methodologies to better understand early cancer detection. Early detection for breast cancer can be a potential benefit in the management of this condition, not only does early treatment make it possible to heal it, but it also prevent its recurrence.\",\"PeriodicalId\":436488,\"journal\":{\"name\":\"2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIT52773.2021.9641284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference in Advances in Power, Signal, and Information Technology (APSIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIT52773.2021.9641284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Study on detection of breast cancer using Machine Learning
Breast cancer is one of the woman's most prominent cancer and most malignant of all cancers. It is the world's largest autopsy of cancer deaths for females and happens in about 3 from 10 people. This article includes numerous machine learning methods and data mining strategies to assess the early detection of breast cancer. Machine learning is used in clinical applications such as identification of cancer cells. The cancerous cells are categorized as Benign and Malignant. This paper analyzes the quality of numerous unsupervised, supervised and other methods for the integrity and prediction for breast cancer. This research could provide various methodologies to better understand early cancer detection. Early detection for breast cancer can be a potential benefit in the management of this condition, not only does early treatment make it possible to heal it, but it also prevent its recurrence.