Does the SVR algorithm using physiological index data improve the accuracy of blood pressure measurement compared to traditional methods?
Machine learning techniques such as the SVR algorithm have the potential to complement and improve the accuracy of traditional blood pressure measurements.
The multi-feature joint training and predicting techniques in machine learning can potentially complement and greatly improve the accuracy of traditional blood pressure measurement, resulting in better disease classification and more accurate clinical judgements.
Zhang et al. (Thu,) studied this question.