Performance Comparison of Multiple Supervised Machine Learning Algorithms for COVID-19 Mortality Prediction

Auishik Pyne, Shamim Anower

Presented at: 2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), 2022
Location: Bhilai, India

Explore how artificial intelligence aids in predicting COVID-19 patient outcomes. Leveraging machine learning models like Logistic Regression and K Nearest Neighbor, this study achieves 95% accuracy and 89% F1 score. Vital for minimizing COVID-19 mortality, this research utilizes John Hopkins University dataset for impactful healthcare solutions.

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