{"title":"通过排名和大学习进行医学社交媒体分析:基于图像的疾病预测研究","authors":"Wei Huang, Peng Zhang, Minmin Shen","doi":"10.1109/SPAC.2014.6982722","DOIUrl":null,"url":null,"abstract":"Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.","PeriodicalId":326246,"journal":{"name":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Medical social media analytics via ranking and big learning: An image-based disease prediction study\",\"authors\":\"Wei Huang, Peng Zhang, Minmin Shen\",\"doi\":\"10.1109/SPAC.2014.6982722\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.\",\"PeriodicalId\":326246,\"journal\":{\"name\":\"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPAC.2014.6982722\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2014 IEEE International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAC.2014.6982722","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medical social media analytics via ranking and big learning: An image-based disease prediction study
Medical social media analytics becomes more and more popular nowadays because of its effectiveness in benefiting diverse health-care applications. In this study, the essential disease prediction task is investigated and realized via medical social media analytics techniques. To be specific, arterial spin labeling (ASL), an emerging functional magnetic resonance imaging modality, is utilized to provide image-based information and novel ranking as well as learning techniques are proposed and incorporated to fulfill the disease prediction task in dementia. To demonstrate its superiority, comprehensive statistical experiments are conducted with comparison to several conventional methods. Promising results are reported from this study.