Machine learning–based prediction of mortality in lung cancer: Application of severity-adjustment method

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Lung cancer has a high incidence and mortality rate, affecting 2.2 million people and causing approximately 1.8 million deaths annually.
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Machine learning technologies are increasingly applied in lung cancer research to improve mortality prediction and identify high-risk patients.
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Comorbidities significantly influence lung cancer survival rates and are essential for accurate mortality risk assessment.
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The study compares machine learning models using comorbidity severity tools (CCI, ACCI, ECI) to enhance mortality prediction for lung cancer patients.
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Existing studies have limitedly explored machine learning approaches for mortality prediction in lung cancer, highlighting a gap in comprehensive evaluations.

Digital Health

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