Using machine learning to predict depression among middle-aged and elderly population in China and conducting empirical analysis.

For depression prediction, factors such as life satisfaction, self-reported health, pain, sleep duration, and cognitive function are identified as highly significant predictive factors. status released display-pdf yes is-olf no is-manuscript no is-preprint no is-journal-matter no is-scanned no is-retracted no Received 2024 Nov 11; Accepted 2025 Jan 29; Collection date 2025. 1 Background introduction Depression is a prevalent mental health issue among the middle-aged and elderly population, associated with a myriad of adverse health outcomes, including impaired sleep quality [ 1 ],cognitive decline [ 2 ],and even an elevated risk of all-cause mortality [ 3 ].

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