Exact(10)
Furthermore, we constructed 3D cancer distribution models from histopathologic information in various slices.
Municipal kidney cancer distribution maps display a marked geographic pattern.
Firstly, mortality is not the best indicator for studying cancer distribution.
This pattern of cancer distribution was not observed in association with ACA or anti-Scl-70 antibodies (data not shown).
Table 1 shows the distribution of the 10 most frequent cancers diagnosed in Denmark [ 23] compared with the cancer distribution by type in our study.
These studies provided evidence of marked intra-regional variability in cancer distribution but did not analyze the incidence of diverse cancers simultaneously.
Similar(50)
GIS have relatively recently been recognized as a useful tool for biomedical research, and in particular for visualizing cancer distributions and estimating the contribution of various environmental risk factors to cancer prevalence [reviewed in [ 1]].
Secondly, we compared the model estimates of cancer mortality distribution with the observed distributions in the regions with good vital records (AmrB, EurA, EurB, EurC and WprA sub regions).
The next most frequent accompanying malignancies were thyroid, liver, breast, urinary bladder, and laryngeal cancers, a distribution similar to cancers in the general Chinese population.
Table 3 Values of test statistics for the remission times of bladder cancer data Distribution Test statistic ((T_{0.99})) New Burr 2.5732 Burr XII 4.4819 Burr II 6.6133 Generalized Burr II 11.0319 Burr X 193.9448.
Comparison with cancer mortality distribution from vital registration confirmed the validity of this approach.
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