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Table 2 | Cancer risk factors associated with methylation of CDKN2A Exposure/cancer risk factor Association with CDKN2A methylation Cancer References

in unknown title
by unknown authors

TABLE 5 Studies of Methylation Capacity and Arsenic-Associated Cancer Study Outcome Key Findings

in unknown title
by unknown authors

Table 1: Part of the cancer database

in MOA: A hybride multidimensional data model for interactive data exploration based on object-relational Analysis Units
by V. Kamp, L. Sitzmann

Table 14: Results for Wisconsin Breast Cancer database

in Unsupervised and Supervised Data Classification via Nonsmooth and Global Optimization
by A. M. Bagirov, A. M. Rubinov, N.V. Soukhoroukova, J. Yearwood 2003
"... In PAGE 39: ...Table14 show that the accuracies of Algorithms 2 and 3 are almost the same, however Algorithm 2 uses significantly less computational efforts. The accuracy of Algorithm 2 two times less than that of Algorithm 1, however the accuracy of Algorithm 1 is still high enough.... ..."
Cited by 2

Table 2. Cancer related bioinformatics databases. Database Name URL Description

in unknown title
by unknown authors
"... In PAGE 5: ... clinical reports and several other aspects of cancer. Table2 lists some of the most prominent databases, which have emerged in respect of cancer research. Some of these databases are discussed below: Cancer Chromosomes database (http://www.... ..."

Table 3: Distribution of cancer indication among Category II genetic tests

in unknown title
by unknown authors 2006
"... In PAGE 19: ...pproval site identified two tests. The 10 most deadly cancers in the U.S. account for 82 percent (40 of 49) of the total test indications; while ovarian cancer accounts for 22 percent (11 of 49) of these indications ( Table3 below). The other cancers being investigated include bladder, cervical/ ... ..."

Table 8. The attributes in the gastric cancer database (Experiment 2).

in Using Rough Sets with Heuristics for Feature Selection
by Ning Zhong, Juzhen Dong, Setsuo Ohsuga 2001
"... In PAGE 12: ... Feature selection must be done for each of tasks. There are 38 attributes (see Table8 ) expect for the obvious unimportant attributes. For each of tasks, we select the feature subset using our approach.... ..."
Cited by 13

Table 1: Attributes in the prostate cancer database. Attribute Description

in Data Mining And Statistics In Medicine: An Application In Prostate Cancer Detection
by Vida Tigrani, George H. John 2005
Cited by 3

Table 5 Results using the Breast-cancer database

in NEUROCOMPUTINC
by George Bebis, Michael Georgiopoulos, Takis Kasparis 1997

Table 10. The results of using LVI to the gastric cancer.

in Using Rough Sets with Heuristics for Feature Selection
by Ning Zhong, Juzhen Dong, Setsuo Ohsuga 2001
"... In PAGE 12: ... If no any inconsistency is found, or the inconsistency is lower than that allowed, the task is accomplished. Table10 shows the results of using LVI to the gastric cancer database with respect to the class: cause of death. In Table 10 Incon denotes the allowed inconsistency, Times denotes the selection times, real Incon denotes the real inconsistency, and Nfeat denotes the number of selected features.... In PAGE 12: ... Table 10 shows the results of using LVI to the gastric cancer database with respect to the class: cause of death. In Table10 Incon denotes the allowed inconsistency, Times denotes the selection times, real Incon denotes the real inconsistency, and Nfeat denotes the number of selected features. In the gastric cancer database, there are 7 inconsistent instances.... ..."
Cited by 13
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