{"title":"基于深度CNN的皮肤癌检测云驱动框架","authors":"Loveleen Gaur, Ujwal Bhatia, Sumedha Bakshi","doi":"10.1109/iciptm54933.2022.9754216","DOIUrl":null,"url":null,"abstract":"Cancer is a potent disease targeting millions of individuals every year. Of all its variants, skin cancer is the most common yet serious. Detection of skin cancer has proven to be a challenge due to the tricky nature of its symptoms. Skin cancer can be prevented and treated at a much early stage by checking the suspicious changes on the skin. Despite medical advancements, the patient's skin is examined mainly in manual ways, susceptible to diagnostic variations among several specialists, and low turnaround time. Added to this is the cost and time of finding a dedicated medical expert. This paper aims to investigate the tumour by applying Deep Convolution Neural Network (CNN) and propose a novel cloud-based service in synchronization with deep learning analysis to bridge the present gap between a patient and a cancer specialist.","PeriodicalId":6810,"journal":{"name":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","volume":"2005 1","pages":"460-464"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Cloud Driven Framework for Skin Cancer Detection using Deep CNN\",\"authors\":\"Loveleen Gaur, Ujwal Bhatia, Sumedha Bakshi\",\"doi\":\"10.1109/iciptm54933.2022.9754216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cancer is a potent disease targeting millions of individuals every year. Of all its variants, skin cancer is the most common yet serious. Detection of skin cancer has proven to be a challenge due to the tricky nature of its symptoms. Skin cancer can be prevented and treated at a much early stage by checking the suspicious changes on the skin. Despite medical advancements, the patient's skin is examined mainly in manual ways, susceptible to diagnostic variations among several specialists, and low turnaround time. Added to this is the cost and time of finding a dedicated medical expert. This paper aims to investigate the tumour by applying Deep Convolution Neural Network (CNN) and propose a novel cloud-based service in synchronization with deep learning analysis to bridge the present gap between a patient and a cancer specialist.\",\"PeriodicalId\":6810,\"journal\":{\"name\":\"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"volume\":\"2005 1\",\"pages\":\"460-464\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iciptm54933.2022.9754216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Innovative Practices in Technology and Management (ICIPTM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iciptm54933.2022.9754216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cloud Driven Framework for Skin Cancer Detection using Deep CNN
Cancer is a potent disease targeting millions of individuals every year. Of all its variants, skin cancer is the most common yet serious. Detection of skin cancer has proven to be a challenge due to the tricky nature of its symptoms. Skin cancer can be prevented and treated at a much early stage by checking the suspicious changes on the skin. Despite medical advancements, the patient's skin is examined mainly in manual ways, susceptible to diagnostic variations among several specialists, and low turnaround time. Added to this is the cost and time of finding a dedicated medical expert. This paper aims to investigate the tumour by applying Deep Convolution Neural Network (CNN) and propose a novel cloud-based service in synchronization with deep learning analysis to bridge the present gap between a patient and a cancer specialist.