An interpretable machine learning model for predicting depression in middle-aged and elderly cancer patients in China: a study based on the CHARLS cohort

We developed a clinical visualization model for health care providers to estimate the risk of depression in middle-aged and elderly cancer patients. As a powerful tool for early identification of depressive symptoms in middle-aged and elderly cancer patients, this model enables medical workers to implement clinical interventions earlier to obtain better clinical benefits.