Copyright
©The Author(s) 2020.
World J Clin Oncol. Nov 24, 2020; 11(11): 918-934
Published online Nov 24, 2020. doi: 10.5306/wjco.v11.i11.918
Published online Nov 24, 2020. doi: 10.5306/wjco.v11.i11.918
Table 3 Demographic characteristics of the sample (n = 177714)
Variable | Mean | SD | Median | n | % |
Survival months/mo | 60.35 | 40.98 | 54.00 | ||
Age at diagnosis/yr | 54.62 | 16.10 | 55.00 | ||
Tumor size/(ID, cm) | 22.56 | 21.74 | 19.00 | ||
Marital status | |||||
Single | 35688 | 20.08 | |||
Married | 110480 | 62.17 | |||
Separated | 1746 | 0.98 | |||
Divorced | 16401 | 9.23 | |||
Widowed | 13055 | 7.35 | |||
Unmarried or domestic partner | 344 | 0.19 | |||
Sex | |||||
Male | 72179 | 40.62 | |||
Female | 105535 | 59.38 | |||
Race | |||||
White | 148556 | 83.60 | |||
Black | 16051 | 9.03 | |||
Other | 13107 | 7.38 |
- Citation: Hung M, Park J, Hon ES, Bounsanga J, Moazzami S, Ruiz-Negrón B, Wang D. Artificial intelligence in dentistry: Harnessing big data to predict oral cancer survival. World J Clin Oncol 2020; 11(11): 918-934
- URL: https://www.wjgnet.com/2218-4333/full/v11/i11/918.htm
- DOI: https://dx.doi.org/10.5306/wjco.v11.i11.918