Apply GM(h,N) Model to Analyze the Influence Factor in Cervical Cancer Screening

Statistical data from the Department of Health, Executive Yuan (the executive branch of the government of the Republic of China) reveals that the rate of cervical cancer is higher than that of any other form of cancers in women. Cervical cancer is currently the fifth COD (Cause of Death) out of all of women cancer mortality in Taiwan. Hence, committing resources for cervical cancer prevention and treatment has become top priority to improve upon the health care of Taiwanese women. This paper tries to analyze the major influence factors with respect to cervical cancer. These concern the differences in rate of screening; rate of abnormality; rate of firm diagnosis; and rate of cure; together with important factors of screened abnormality. Ours is the pre-study for establishing an Integrated Assessment Model for Promoting Firm Diagnosis Rate of Patients with Cervical Cancer. Initially, we based this on an evaluation model that considered five factors as our object of study: (1) age group, (2) educational background, (3) contraception condition, (4) menstruation, and (5). results of the morbidity diagnosis. Our approach deviates from the traditional method since we now use the multivariable Grey model GM(h,N) to analyze the whole data, and by this means we find the weighting for the first four of the aforementioned factors, to correspond with the fifth one (the results of the morbidity diagnosis). The data was too large to analyze with the standard computational toolbox, so we additionally developed a Matlab toolbox. Not only did we succeed to use it to obtain the rank influence factor for cervical cancer, but it can now be used to extend the applicability of the GM(h,N) model to other medical disciplines.