Abstract
Healthcare is the cardinal component on which the foundation of human welfare can be laid. Healthcare research mainly focuses on the healthy living standards of individuals. Relationship between pulmonary embolism and cardiac arrest is presented in this paper. The proposed research is divided into two phases. The first phase includes the establishment of connectivity between the two medical fields which is done by finding out the relationship between the pulse pressure and stroke volume. The second phase includes the application and comparison of machine learning algorithms 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. Also the comparison between the boosting and bagging classifier has been done.
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Firdous, N., Bhardwaj, S., Bhat, A.H. (2021). Exploring Feature Selection Using Supervised Machine Learning Algorithms for Establishing a Link Between Pulmonary Embolism and Cardiac Arrest. In: Singh Pundir, A.K., Yadav, A., Das, S. (eds) Recent Trends in Communication and Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-0167-5_1
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DOI: https://doi.org/10.1007/978-981-16-0167-5_1
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