DocumentCode
3083141
Title
Generalized Caseview applied to prostate cancer prognosis
Author
Levy, Pierre P. ; Bardier, Armelle ; Doublet, Jean-Dominique ; Sibony, Mathilde
Author_Institution
Public Health Department Hÿpital Tenon, Assistance Publique Hÿpitaux de Paris, 4 rue de la Chine, 75970, Cedex 20, France
fYear
2008
fDate
20-25 Aug. 2008
Firstpage
5129
Lastpage
5131
Abstract
The interpretation of results of any study using large tables with series of numbers is always difficult. Generalized Case View Method (GCm) allows translating these tables of numbers into an image. The Method identifies each informational entity in the table with a “pixel”, forming what we call an “infoxel”. The sum of all informational entities becomes an image, the Generalized Caseview. The method consists of two steps: the first one is to define the reference frame while the second is to visualize data through the reference frame. The “infoxels” that constitute the reference frame should be organized according to three criteria: binary, nominal and ordinal. Here this method has been applied to visualize the results of a study about prostate cancer spread. This paper exemplifies the usefulness of associating a classical statistical tool with Generalized Caseview method to solve a biomedical problem.
Keywords
Anatomy; Biomedical imaging; Biopsy; Data visualization; Histograms; Pathology; Prostate cancer; Public healthcare; Statistical analysis; Tumors; Artificial Intelligence; Biopsy; Computer Graphics; Decision Support Systems, Clinical; Diagnosis, Computer-Assisted; Humans; Male; Pattern Recognition, Automated; Prostatic Neoplasms; Reproducibility of Results; Sensitivity and Specificity; User-Computer Interface;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
Conference_Location
Vancouver, BC
ISSN
1557-170X
Print_ISBN
978-1-4244-1814-5
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2008.4650368
Filename
4650368
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