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Download PDFOpen PDF in browserCOVID-19 Prediction through CNN and LSTM Deep Learning ModelsEasyChair Preprint 80077 pages•Date: May 22, 2022AbstractThe advances in the medical field have been crucial for the purpose of attaining the improvement in the the health of the masses. A healthy populous for a nation has the ability to achieve the goals of productivity while reducing the efforts to combat the spread of diseases and other communicable ailments. If the majority of the individuals are healthy and have a healthy lifestyle, it would be far easier to recover from a pandemic and also achieve effective realizations that can be useful in achieving the growth and advancements far more efficiently. The recent pandemic is a testament to this fact, the Covid-19 virus has led to the largescale deaths and destruction across the world. This pandemic could have been better handled if the healthcare sector had an idea about the scale and the severity of the pandemic which would let them be effectively-prepared in response to the increasing infections. The progression of a pandemic is extremely complicated which can only be predicted using machine-learning implementations. For this purpose, this research article deploys Pearson correlation and K Nearest Neighbor clustering along with the Convolutional Neural Networks and Decision Tree for precise Covid-19 predictions. The experimental outcomes have proved the improvement offered by the presented approach over conventional implementations. Keyphrases: COVID-19 prediction, Convolution Neural Network, K- Nearest neighbor Classifications, LSTM, Pearson correlation Download PDFOpen PDF in browser |
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