Machine Learning to Construct an Association Model for Lung Cancer and Environmental Hormone

Pei-Hung Liao

Status: Active, not recruiting

Conditions: Lung Neoplasms

Study type: Observational

Funder types: Other

Identifiers

NCT06259461

202204055RINA

Details and patient eligibility

About

To apply machine learning to construct an association model regarding lung cancer and environmental hormones to more comprehensively identify factors that may lead to lung cancer and to improve existing lung cancer nursing assessments.

Full description

The present study is exploratory, and its design was divided into three stages: Stage 1 explored the environmental hormonal risk factors for lung cancer and constructed an association model using machine learning algorithms. Stage 2 validated the results of the association model with better predictive results in clinical settings. Stage 3 involved recommendations for reconstructing nursing assessments based on the results of the clinical model validation. The three stages are summarized as follows.

Enrollment: 128 estimated patients

Sex: All

Ages: 20+ years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

1. 20 years or older;
2. conscious, without mental disorders;
3. able to use Mandarin to communicate, had a smartphone or tablet computer and could operate it by themselves,
4. and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.

Exclusion criteria

• The exclusion criteria were those who could not understand the content of the nursing assessment questions and those with mental disorders.