Applying machine learning to construct an association model for lung cancer and environmental hormone high‐risk factors and nursing assessment reconstruction

Author:

Lee Pin‐Chieh1,Lin Mong‐Wei2,Liao Hsien‐Chi3,Lin Chan‐Yi4,Liao Pei‐Hung5ORCID

Affiliation:

1. Department of Nursing National Taiwan University Cancer Center Taipei Taiwan

2. Department of Surgery, Division of Thoracic Surgery, Department of Surgery College of Medicine, National Taiwan University, National Taiwan University Hospital Taipei Taiwan

3. College of Medicine, Department of Traumatology National Taiwan University, National Taiwan University Hospital Taipei Taiwan

4. Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan

5. School of Nursing National Taipei University of Nursing and Health Sciences Taipei Taiwan

Abstract

AbstractIntroductionTo utilize machine learning techniques to develop an association model linking lung cancer and environmental hormones to enhance the understanding of potential lung cancer risk factors and refine current nursing assessments for lung cancer.DesignThis study is exploratory in nature. In Stage 1, data were sourced from a biological database, and machine learning methods, including logistic regression and neural‐like networks, were employed to construct an association model. Results indicate significant associations between lung cancer and blood cadmium, urine cadmium, urine cadmium/creatinine, and di(2‐ethylhexyl) phthalate. In Stage 2, 128 lung adenocarcinoma patients were recruited through convenience sampling, and the model was validated using a questionnaire assessing daily living habits and exposure to environmental hormones.ResultsAnalysis reveals correlations between the living habits of patients with lung adenocarcinoma and exposure to blood cadmium, urine cadmium, urine cadmium/creatinine, polyaromatic hydrocarbons, diethyl phthalate, and di(2‐ethylhexyl) phthalate.ConclusionsAccording to the World Health Organization's global statistics, lung cancer claims approximately 1.8 million lives annually, with more than 50% of patients having no history of smoking or non‐traditional risk factors. Environmental hormones have garnered significant attention in recent years in pathogen exploration. However, current nursing assessments for lung cancer risk have not incorporated environmental hormone‐related factors. This study proposes reconstructing existing lung cancer nursing assessments with a comprehensive evaluation of lung cancer risks.Clinical RelevanceThe findings underscore the importance of future studies advocating for public screening of environmental hormone toxins to increase the sample size and validate the model externally. The developed association model lays the groundwork for advancing cancer risk nursing assessments.

Publisher

Wiley

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