A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports
Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on (2011)
San Jose, CAlifornia USA
July 26, 2011 to July 29, 2011
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/HISB.2011.4
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.
information retrieval, genetic algorithm, wavelets, radiology
C. C. Rojas, B. G. Beckerman, R. M. Patton and T. E. Potok, "A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports," Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on(HISB), San Jose, CAlifornia USA, 2011, pp. 104-111.