Breast Adenocarcinoma, Breast Diseases
Conditions
Keywords
Machine learning; association model; environmental hormones; breast cancer
Brief summary
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.
Detailed description
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.
Interventions
None listed
Sponsors
Pei-Hung Liao
Study design
Observational model
CASE_ONLY
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
FEMALE
Age
20 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* (1) patients aged 20 years or above; (2) patients with breast cancer.
Exclusion criteria
* non-patients with breast cancer
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| established an association model between environmental hormones and breast cancer | 2015~2024 | The basic personal information of the participants included gender, age, height, weight, past disease history, family history, reproductive history, postoperative medication, chemotherapy type, breast cancer pathology type, stage, etc. |
Countries
Taiwan
Outcome results
None listed