Next-visit prediction and prevention of hypertension using large-scale routine health checkup data.

ABSTRACT: This paper proposes the use of machine learning models to predict one's risk of having hypertension in the future using their routine health checkup data of their current and past visits to a health checkup center. The large-scale and high-dimensional dataset used in this study comes from MJ Health Research Foundation in Taiwan. The training data for models is separated into 5 folds and used to train 5 models in a 5-fold cross validation manner. While predicting the results for the test set, the voted result of 5 models is used as the final prediction. Experimental results show that our models achieve 69.59% of precision, 77.90% of recall, and 73.51% of F1-score, which outperforms a baseline using only the blood pressure of visitors' last visits. Experiments also show that a visitor who pe

SUBMITTER: Wang CC 

PROVIDER: S-EPMC11560048 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature