Title: Prevention of autopsy by establishing a cause-effect relationship between pulmonary embolism and heart-failure using machine learning

Authors: Naira Firdous; Sushil Bhardwaj; Amjad Husain Bhat

Addresses: Department of Computer Engineering, RIMT University, Punjab, India ' Department of Computer Engineering, RIMT University, Punjab, India ' Department of Computer Engineering, RIMT University, Punjab, India

Abstract: This paper presents a Cause Effect Relationship between Heart Failure and Pulmonary Embolism using Machine Learning. The proposed research is divided into two parts. The first part includes the establishment of connectivity between the two medical fields which is done by finding out the relationship between the pulse pressure and the stroke volume. The second phase includes the implementation of machine learning on the above formed connectivity. Univariate technique of feature selection is performed initially in order to get the most relevant attributes. Overfitting problem has been addressed by formulating an ensemble model by making use of hard and soft voting classifiers. Also, efficiency has been checked by increasing the number of hidden layers of a neural network.

Keywords: pulmonary embolism; stroke volume; pulse pressure; systolic; diastolic; overfitting; ensemble classifiers; neural-network.

DOI: 10.1504/IJCAT.2021.119769

International Journal of Computer Applications in Technology, 2021 Vol.66 No.2, pp.165 - 171

Received: 21 Jul 2020
Accepted: 22 Nov 2020
Published online: 20 Dec 2021 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article