Machine learning evaluation of a hypertension screening program in a university workforce over five years.

ABSTRACT: The global prevalence of hypertension continues excessively elevated, especially among low- and middle-income nations. Workplaces provide tremendous opportunities as a unique, easily accessible and practical avenue for early diagnosis and treatment of hypertension among the workforce class. The evaluation of such a Workplace Screening Strategy can give insight into its possible effects. Innovative machine learning approaches like k-means clustering are underutilized for such assessments. We set out to use this technology to analyze the results of our university's yearly health checkup of the employees for hypertension. An anonymized dataset including the demographics and blood pressure monitoring information gathered from workers in various departments/units of a learning organization. The

SUBMITTER: Adeleke O 

PROVIDER: S-EPMC11618500 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature