investigated the association model between environmental hormone-related living habits and breast cancer, as well as dietary improvement programs through machine learning and clinical validation of patients with breast cancer.

Female breast cancer is the second most common cancer worldwide and the age at diagnosis is decreasing. Traditional risk factor screening for breast cancer focuses on reproductive history, family history, age at menarche, and age at menopause; however, young patients diagnosed with breast cancer who do not meet the above risk factors are becoming common.This study established an association model between environmental hormones and breast cancer through machine learning to improve dietary programs to reduce the incidence of breast cancer.

Inclusion Criteria:

• (1) patients aged 20 years or above; (2) patients with breast cancer.

Exclusion Criteria:

• non-patients with breast cancer

This study recruited research subjects from an outpatient clinic and ward of the Department of General Surgery of the Cheng Hsing General Hospital.