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2011 IEEE First International Conference on Healthcare Informatics, Imaging and Systems Biology
A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports
San Jose, CAlifornia USA
July 26-July 29
ISBN: 978-0-7695-4407-6
| ASCII Text | x | ||
| Robert M. Patton, Carlos C. Rojas, Barbara G. Beckerman, Thomas 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, pp. 104-111, 2011 IEEE First International Conference on Healthcare Informatics, Imaging and Systems Biology, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/HISB.2011.4, author = {Robert M. Patton and Carlos C. Rojas and Barbara G. Beckerman and Thomas E. Potok}, title = {A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports}, journal ={Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on}, volume = {0}, year = {2011}, isbn = {978-0-7695-4407-6}, pages = {104-111}, doi = {http://doi.ieeecomputersociety.org/10.1109/HISB.2011.4}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on TI - A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports SN - 978-0-7695-4407-6 SP104 EP111 A1 - Robert M. Patton, A1 - Carlos C. Rojas, A1 - Barbara G. Beckerman, A1 - Thomas E. Potok, PY - 2011 KW - information retrieval KW - genetic algorithm KW - wavelets KW - radiology VL - 0 JA - Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on ER - | |||
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.
Index Terms:
information retrieval, genetic algorithm, wavelets, radiology
Citation:
Robert M. Patton, Carlos C. Rojas, Barbara G. Beckerman, Thomas E. Potok, "A Computational Framework for Search, Discovery, and Trending of Patient Health in Radiology Reports," hisb, pp.104-111, 2011 IEEE First International Conference on Healthcare Informatics, Imaging and Systems Biology, 2011
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