Artificial plant optimization algorithm to detect heart rate & presence of heart disease using machine learning

作者：

Highlights：

• ‘Modified Artificial Plant Optimization algorithm (MAPO)’ has been discussed for detection of heart rate using fingertip video.

• Various machine learning algorithms have been applied on Heart Disease dataset to calculate presence of heart disease.

• The proposed MAPO shows better accuracies than other related works with the highest number of videos (84 out of 100) which has relative errors less than 5%.

• It achieved the Pearson Correlation and Standard Error of Estimate as 0.9541 and 2.418 respectively while detecting heart rate.

摘要

•‘Modified Artificial Plant Optimization algorithm (MAPO)’ has been discussed for detection of heart rate using fingertip video.•Various machine learning algorithms have been applied on Heart Disease dataset to calculate presence of heart disease.•The proposed MAPO shows better accuracies than other related works with the highest number of videos (84 out of 100) which has relative errors less than 5%.•It achieved the Pearson Correlation and Standard Error of Estimate as 0.9541 and 2.418 respectively while detecting heart rate.

论文关键词：Modified artificial plant optimization algorithm,Machine learning,Savitzky-Golay filter,Extreme gradient boosting,Artificial neural network

论文评审过程：Received 4 June 2019, Revised 30 October 2019, Accepted 2 November 2019, Available online 8 November 2019, Version of Record 22 November 2019.

论文官网地址：https://doi.org/10.1016/j.artmed.2019.101752