The invention discloses an in-vitro fertilization
failure risk prediction model and a construction method and a prediction method thereof, based on data of an ART treatment cycle, multi-dimensional indexes such as woman age, BMI, male seminal fluid parameters and
infertility years are incorporated,
logistic regression, a
random forest and an XGBoost model are constructed, and performance is evaluated by adopting a nested
cross validation framework (including an SMOTE technology). Results show that the
logistic regression model is optimal in performance and is remarkably superior to a
random forest model and an XGBoost model, key predictive factors include male age, female BMI, the total number of forward motional sperms and a
sperm DNA fragmentation index, the total number of forward motional sperms and the male age are protection factors, the BMI and the
sperm DNA fragmentation index are risk factors, and the risk factors are the risk factors. The C-index of the model column diagram is up to 0.722 through internal
verification, and the model column diagram has the clinical distinguishing capability of medium or above. The
logistic regression model is verified to have high efficiency and stability in IVF fertilization failure prediction, and can provide decision support for clinical early intervention.