M. M. Daud, W. Zaki, A. Hussain, Wan Siti Halimatul Munirah Wan Ahmad, H. A. Mutalib
{"title":"使用智能手机的联网眼部筛查系统","authors":"M. M. Daud, W. Zaki, A. Hussain, Wan Siti Halimatul Munirah Wan Ahmad, H. A. Mutalib","doi":"10.1109/ICKII.2018.8569141","DOIUrl":null,"url":null,"abstract":"This article presents an extensive survey of recent studies on mobile applications for ocular diseases detection. Survey results show that smartphone applications are the current niche in healthcare, particularly in the diagnosis of ocular diseases. This environment has led to the development of the proposed framework of a corneal disease screening system using mobile phones to overcome the aforementioned limitations. Typically, such systems are integrated with the Internet of Things and image processing with machine learning techniques to process the anterior segment of photographed images. Thus, they are able to serve as automatic systems to assist optometrists in clinical diagnosis.","PeriodicalId":170587,"journal":{"name":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Connected Ocular Screening System Using Smartphones\",\"authors\":\"M. M. Daud, W. Zaki, A. Hussain, Wan Siti Halimatul Munirah Wan Ahmad, H. A. Mutalib\",\"doi\":\"10.1109/ICKII.2018.8569141\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents an extensive survey of recent studies on mobile applications for ocular diseases detection. Survey results show that smartphone applications are the current niche in healthcare, particularly in the diagnosis of ocular diseases. This environment has led to the development of the proposed framework of a corneal disease screening system using mobile phones to overcome the aforementioned limitations. Typically, such systems are integrated with the Internet of Things and image processing with machine learning techniques to process the anterior segment of photographed images. Thus, they are able to serve as automatic systems to assist optometrists in clinical diagnosis.\",\"PeriodicalId\":170587,\"journal\":{\"name\":\"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICKII.2018.8569141\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICKII.2018.8569141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Connected Ocular Screening System Using Smartphones
This article presents an extensive survey of recent studies on mobile applications for ocular diseases detection. Survey results show that smartphone applications are the current niche in healthcare, particularly in the diagnosis of ocular diseases. This environment has led to the development of the proposed framework of a corneal disease screening system using mobile phones to overcome the aforementioned limitations. Typically, such systems are integrated with the Internet of Things and image processing with machine learning techniques to process the anterior segment of photographed images. Thus, they are able to serve as automatic systems to assist optometrists in clinical diagnosis.