Xun Wang , Yahan Yang , Yuxuan Wu , Wenbin Wei , Li Dong , Yang Li , Xingping Tan , Hankun Cao , Hong Zhang , Xiaodan Ma , Qin Jiang , Yunfan Zhou , Weihua Yang , Chaoyu Li , Yu Gu , Lin Ding , Yanli Qin , Qi Chen , Lili Li , Mingyue Lian , Haotian Lin
{"title":"国家多中心人工智能近视防治项目","authors":"Xun Wang , Yahan Yang , Yuxuan Wu , Wenbin Wei , Li Dong , Yang Li , Xingping Tan , Hankun Cao , Hong Zhang , Xiaodan Ma , Qin Jiang , Yunfan Zhou , Weihua Yang , Chaoyu Li , Yu Gu , Lin Ding , Yanli Qin , Qi Chen , Lili Li , Mingyue Lian , Haotian Lin","doi":"10.1016/j.imed.2021.05.001","DOIUrl":null,"url":null,"abstract":"<div><p>In recent years, the incidence of myopia has increased at an alarming rate among children and adolescents in China. The exploration of an effective prevention and control method for myopia is in urgent need. With the development of information technology in the past decade, artificial intelligence with the Internet of Things technology (AIoT) is characterized by strong computing power, advanced algorithm, continuous monitoring, and accurate prediction of long-term progression. Therefore, big data and artificial intelligence technology have the potential to be applied to data mining of myopia etiology and prediction of myopia occurrence and development. More recently, there has been a growing recognition that myopia study involving AIoT needs to undergo a rigorous evaluation to demonstrate robust results.</p></div>","PeriodicalId":73400,"journal":{"name":"Intelligent medicine","volume":"1 2","pages":"Pages 51-55"},"PeriodicalIF":4.4000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.imed.2021.05.001","citationCount":"2","resultStr":"{\"title\":\"The national multi-center artificial intelligent myopia prevention and control project\",\"authors\":\"Xun Wang , Yahan Yang , Yuxuan Wu , Wenbin Wei , Li Dong , Yang Li , Xingping Tan , Hankun Cao , Hong Zhang , Xiaodan Ma , Qin Jiang , Yunfan Zhou , Weihua Yang , Chaoyu Li , Yu Gu , Lin Ding , Yanli Qin , Qi Chen , Lili Li , Mingyue Lian , Haotian Lin\",\"doi\":\"10.1016/j.imed.2021.05.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>In recent years, the incidence of myopia has increased at an alarming rate among children and adolescents in China. The exploration of an effective prevention and control method for myopia is in urgent need. With the development of information technology in the past decade, artificial intelligence with the Internet of Things technology (AIoT) is characterized by strong computing power, advanced algorithm, continuous monitoring, and accurate prediction of long-term progression. Therefore, big data and artificial intelligence technology have the potential to be applied to data mining of myopia etiology and prediction of myopia occurrence and development. More recently, there has been a growing recognition that myopia study involving AIoT needs to undergo a rigorous evaluation to demonstrate robust results.</p></div>\",\"PeriodicalId\":73400,\"journal\":{\"name\":\"Intelligent medicine\",\"volume\":\"1 2\",\"pages\":\"Pages 51-55\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.imed.2021.05.001\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Intelligent medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2667102621000085\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligent medicine","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667102621000085","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
The national multi-center artificial intelligent myopia prevention and control project
In recent years, the incidence of myopia has increased at an alarming rate among children and adolescents in China. The exploration of an effective prevention and control method for myopia is in urgent need. With the development of information technology in the past decade, artificial intelligence with the Internet of Things technology (AIoT) is characterized by strong computing power, advanced algorithm, continuous monitoring, and accurate prediction of long-term progression. Therefore, big data and artificial intelligence technology have the potential to be applied to data mining of myopia etiology and prediction of myopia occurrence and development. More recently, there has been a growing recognition that myopia study involving AIoT needs to undergo a rigorous evaluation to demonstrate robust results.