Birmingham, United Kingdom

Visit us

Blog

Machine learning improves the prediction of febrile neutropenia in Korean inpatients undergoing chemotherapy for breast cancer

In the present study, multivariate analysis demonstrated predictive factors for FN, including age, staging, and taxane-based regimen. The lymphocyte count 5 days after chemotherapy was also a strong predictive factor for FN. Based on these findings, logistic regression showed an AUC of 0.870 for validation.

Source: Machine learning improves the prediction of febrile neutropenia in Korean inpatients undergoing chemotherapy for breast cancer