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Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports.

机译：放射学报告中患者健康的搜索，发现和趋势的计算框架。

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The healthcare industry as a whole lags far behind other industries in terms of knowledge discovery capabilities. There are many piece-wise approaches to analysis of patient records. Unfortunately, there are few approaches that enable a completely automated approach that supports not just search, but also discovery and prediction of patient health. The work presented here describes a computational framework that provides near complete automation of the discovery and trending of patient characteristics. This approach has been successfully applied to the domain of mammography, but could be applied to other domains of radiology with minimal effort.

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Patton, R. M.; Rojas, C. C.; Beckerman, B. G.; Potok, T. E.;
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年度 2013
页码 1-8
总页数 8
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Patients; Health status; Radiology; Algorithms; Biology; Mammography; Records(Files); Trends;

机译：患者;健康状况;放射学;算法;生物学;乳房摄影;记录（文件）;趋势;

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4. A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports [C] . Patton Robert M., Rojas Carlos C., Beckerman Barbara G., 2011 First IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology . 2011

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5. Towards a canonical representation for machine understanding of natural language in radiology reports. [D] . Bashyam, Vijayaraghavan. 2008

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Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports.

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