Predicting hypertension without measurement: A non-invasive, questionnaire-based approach

作者：

Highlights：

• A questionnaire-based, non-invasive approach is proposed to predict hypertension.

• We detail the selection of artificial neural networks architecture in actual use.

• Under-sampling with K-means algorithm is proposed to balance the dataset.

• Experimental results demonstrate the feasibility of the proposed approach.

• The proposed approach can be used to analyze other chronic diseases.

摘要

•A questionnaire-based, non-invasive approach is proposed to predict hypertension.•We detail the selection of artificial neural networks architecture in actual use.•Under-sampling with K-means algorithm is proposed to balance the dataset.•Experimental results demonstrate the feasibility of the proposed approach.•The proposed approach can be used to analyze other chronic diseases.

论文关键词：Hypertension prediction,Non-invasive,Questionnaire,Behavior Risk Factor Surveillance System,Artificial neural networks

论文评审过程：Available online 11 June 2015, Version of Record 24 June 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.06.012