Predicting diagnosis and survival of bone metastasis in breast cancer using machine learning.

ABSTRACT: This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver

SUBMITTER: Zhong X 

PROVIDER: S-EPMC10600146 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature