Why the study?
Risk prediction models frequently identify individuals at risk of hypertension, prompting an evaluation of machine learning algorithms compared with the conventional Cox PH model using survival data.
Do machine learning algorithms improve the prediction of hypertension incidence compared to conventional Cox proportional hazards models in a general population cohort?
Do machine learning algorithms improve the prediction of hypertension incidence compared to conventional Cox proportional hazards models in a general population cohort?
Machine learning algorithms perform similarly to conventional Cox proportional hazards regression models for predicting hypertension incidence in a moderate-sized dataset.
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ML algorithms match Cox PH accuracy for hypertension prediction in moderate cohorts; leaves open added value in larger or high-dimensional datasets.
Leung et al. (2023) studied this question.
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