An observational study in Lung Neoplasms, sponsored by Pei-Hung Liao. Active, not recruiting at 2 sites in Taiwan. Open to participants aged 20 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-02-14.
Sponsored by Pei-Hung Liao · Observational
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.
7,243 studies on the registry are indexed under Lung Neoplasms; 1,557 are open to participants now.
This study's planned enrollment of 128 is below the median of 189 across 1,514 observational studies indexed under Lung Neoplasms.
Browse Lung Neoplasms studies →Pei-Hung Liao is the lead sponsor of 4 studies on the registry; none are open to participants now.
Counted across the registry records on this site, refreshed daily.
The study focused on lung cancer cases and investigated the association with exposure to environmental hormones
Exclusion Criteria:
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
Time frame: the database research samples from May 2014 to December 2020.
Plan to share: No
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This study is active, not recruiting, as verified in Feb 2024. You cannot join it, but the record below documents what was studied.
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Pei-Hung Liao