Roshan Bhandari, Rishikesh V Phatangare, Mark A Eckert, Kenneth I Vaden, James Z Wang
{"title":"阅读障碍数据联盟存储库:研究数据共享和交付平台。","authors":"Roshan Bhandari, Rishikesh V Phatangare, Mark A Eckert, Kenneth I Vaden, James Z Wang","doi":"10.1007/978-3-031-43075-6_15","DOIUrl":null,"url":null,"abstract":"<p><p>Specific learning disability of reading, or dyslexia, affects 5-17% of the population in the United States. Research on the neurobiology of dyslexia has included studies with relatively small sample sizes across research sites, thus limiting inference and the application of novel methods, such as deep learning. To address these issues and facilitate open science, we developed an online platform for data-sharing and advanced research programs to enhance opportunities for replication by providing researchers with secondary data that can be used in their research (https://www.dyslexiadata.org). This platform integrates a set of well-designed machine learning algorithms and tools to generate secondary datasets, such as cortical thickness, as well as regional brain volume metrics that have been consistently associated with dyslexia. Researchers can access shared data to address fundamental questions about dyslexia and development, replicate research findings, apply new methods, and educate the next generation of researchers. The overarching goal of this platform is to advance our understanding of a disorder that has significant academic, social, and economic impacts on children, their families, and society.</p>","PeriodicalId":516866,"journal":{"name":"Brain informatics : 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings. International Conference on Brain Informatics (16th : 2023 : Hoboken, N.J.)","volume":"13974 ","pages":"167-178"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10859776/pdf/","citationCount":"0","resultStr":"{\"title\":\"Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research.\",\"authors\":\"Roshan Bhandari, Rishikesh V Phatangare, Mark A Eckert, Kenneth I Vaden, James Z Wang\",\"doi\":\"10.1007/978-3-031-43075-6_15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Specific learning disability of reading, or dyslexia, affects 5-17% of the population in the United States. Research on the neurobiology of dyslexia has included studies with relatively small sample sizes across research sites, thus limiting inference and the application of novel methods, such as deep learning. To address these issues and facilitate open science, we developed an online platform for data-sharing and advanced research programs to enhance opportunities for replication by providing researchers with secondary data that can be used in their research (https://www.dyslexiadata.org). This platform integrates a set of well-designed machine learning algorithms and tools to generate secondary datasets, such as cortical thickness, as well as regional brain volume metrics that have been consistently associated with dyslexia. Researchers can access shared data to address fundamental questions about dyslexia and development, replicate research findings, apply new methods, and educate the next generation of researchers. The overarching goal of this platform is to advance our understanding of a disorder that has significant academic, social, and economic impacts on children, their families, and society.</p>\",\"PeriodicalId\":516866,\"journal\":{\"name\":\"Brain informatics : 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings. International Conference on Brain Informatics (16th : 2023 : Hoboken, N.J.)\",\"volume\":\"13974 \",\"pages\":\"167-178\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10859776/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Brain informatics : 16th International Conference, BI 2023, Hoboken, NJ, USA, August 1-3, 2023, Proceedings. 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Dyslexia Data Consortium Repository: A Data Sharing and Delivery Platform for Research.
Specific learning disability of reading, or dyslexia, affects 5-17% of the population in the United States. Research on the neurobiology of dyslexia has included studies with relatively small sample sizes across research sites, thus limiting inference and the application of novel methods, such as deep learning. To address these issues and facilitate open science, we developed an online platform for data-sharing and advanced research programs to enhance opportunities for replication by providing researchers with secondary data that can be used in their research (https://www.dyslexiadata.org). This platform integrates a set of well-designed machine learning algorithms and tools to generate secondary datasets, such as cortical thickness, as well as regional brain volume metrics that have been consistently associated with dyslexia. Researchers can access shared data to address fundamental questions about dyslexia and development, replicate research findings, apply new methods, and educate the next generation of researchers. The overarching goal of this platform is to advance our understanding of a disorder that has significant academic, social, and economic impacts on children, their families, and society.