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18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)
Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data
Dublin, Ireland
June 23-June 24
ISBN: 0-7695-2355-2
| ASCII Text | x | ||
| Stewart McGrenary, Brian F. O?Reilly, John J. Soraghan, "Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data," 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS), pp. 587-592, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005. | |||
| BibTex | x | ||
| @article{ 10.1109/CBMS.2005.78, author = {Stewart McGrenary and Brian F. O?Reilly and John J. Soraghan}, title = {Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data}, journal ={2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS)}, volume = {0}, year = {2005}, issn = {1063-7125}, pages = {587-592}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.78}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS) TI - Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data SN - 1063-7125 SP587 EP592 A1 - Stewart McGrenary, A1 - Brian F. O?Reilly, A1 - John J. Soraghan, PY - 2005 KW - null VL - 0 JA - 2012 25th IEEE International Symposium on Computer-Based Medical Systems (CBMS) ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.78
Facial Paralysis is a debilitating condition in which sufferers experience unilateral paralysis of the left or right facial nerve. An evidence based assessment of a patient?s condition is almost impossible because all current grading scales are subjective. A quantitative, practical, reliable system would be an invaluable tool in this field of neurootology. Demonstrated here is a system which intelligently quantifies the facial damage in 43 testing videos from 14 subjects. Using an Artificial Neural Network the average mean squared error for the system is 1.6%.
Citation:
Stewart McGrenary, Brian F. O?Reilly, John J. Soraghan, "Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data," cbms, pp.587-592, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005
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