In today’s world, cardiovascular diseases are prevalent becoming the leading cause of death; more than half of the cardiovascular diseases are due to Coronary Heart Disease (CHD) which generates the demand of predicting them timely so that people can take precautions or treatment before it becomes fatal. For serving this purpose a Modified Artificial Plant Optimization (MAPO) algorithm has been proposed which can be used as an optimal feature selector along with other machine learning algorithms to predict the heart rate using the fingertip video dataset which further predicts the presence or absence of Coronary Heart Disease in an individual at the moment. Initially, the video dataset has been pre-processed, noise is filtered and then MAPO is applied to predict the heart rate with a Pearson correlation and Standard Error Estimate of 0.9541 and 2.418 respectively. The predicted heart rate is used as a feature in other two datasets and MAPO is again applied to optimize the features of both datasets. Different machine learning algorithms are then applied to the optimized dataset to predict values for presence of current heart disease. The result shows that MAPO reduces the dimensionality to the most significant information with comparable accuracies for different machine learning models with maximum dimensionality reduction of 81.25%. MAPO has been compared with other optimizers and outperforms them with better accuracy.

在当今世界，心血管疾病正成为导致死亡的首要原因。超过一半的心血管疾病是由冠心病（CHD）引起的，冠心病要求及时进行预测，以便人们在死亡之前可以采取预防措施或治疗。为了达到这个目的，已经提出了一种改进的人工植物优化（MAPO）算法，该算法可以与其他机器学习算法一起用作最佳特征选择器，以使用指尖视频数据集来预测心率，该数据集可以进一步预测冠状动脉的存在或不存在此刻个人患有心脏病。最初，对视频数据集进行了预处理，对噪声进行了滤波，然后应用MAPO预测心率，其皮尔逊相关性和标准误差估计值为0.9541和2。分别为418。预测的心率在其他两个数据集中用作特征，并且MAPO再次用于优化两个数据集的特征。然后将不同的机器学习算法应用于优化的数据集，以预测当前心脏病的存在值。结果表明，对于不同的机器学习模型，MAPO将维降到最重要的信息，并且具有相当的精度，最大维降为81.25％。MAPO已与其他优化器进行了比较，并以更好的精度胜过它们。然后将不同的机器学习算法应用于优化的数据集，以预测当前心脏病的存在值。结果表明，对于不同的机器学习模型，MAPO将维降到最重要的信息，并且具有相当的精度，最大维降为81.25％。MAPO已与其他优化器进行了比较，并以更好的精度胜过它们。然后将不同的机器学习算法应用于优化的数据集，以预测当前心脏病的存在值。结果表明，对于不同的机器学习模型，MAPO将维降到最重要的信息，并且具有相当的精度，最大维降为81.25％。MAPO已与其他优化器进行了比较，并以更好的精度胜过它们。