Based on biomedical index data: Risk prediction model for prostate cancer.

ABSTRACT:

Abstract

To explore the influencing factors of prostate cancer occurrence, set up risk prediction model, require reference for the preliminary diagnosis of clinical doctors, this model searched database through the data of prostate cancer patients and prostate hyperplasia patients National Clinical Medical Science Data Center.With the help of Stata SE 12.0 and SPSS 25.0 software, the biases between groups were balanced by propensity score matching. Based on the matched data, the relevant factors were further screened by stepwise logistic regression analysis, the key variable and artificial neural network model are established. The prediction accuracy of the model is evaluated by combining the probability of test set with the area under receiver operating characteristic curve (ROC).

SUBMITTER: Guo H 

PROVIDER: S-EPMC8084031 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature