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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.
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.
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| Measure | Description | Time Frame |
|---|---|---|
| identify factors that may lead to lung cancer and environmental hormones. | This association model can assist in identifying the risk groups of lung cancer and advising physicians on the appropriate environmental hormone testing and treatment to provide nursing guidance and medical advice | the database research samples from May 2014 to December 2020. |
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Inclusion Criteria:
Exclusion Criteria:
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The study focused on lung cancer cases and investigated the association with exposure to environmental hormones
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Taipei university of nursing and health science | Taipei | Taiwan | ||||
| National Taiwan University, Cancer Center |
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| ID | Term |
|---|---|
| D008175 | Lung Neoplasms |
| ID | Term |
|---|---|
| D012142 | Respiratory Tract Neoplasms |
| D013899 | Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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(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, and were willing to participate in the study after the reasons for participation were explained and a consent form was signed, indicating their consent.
| Taipei |
| Taiwan |
| D008171 |
| Lung Diseases |
| D012140 | Respiratory Tract Diseases |