Prediction Of Long Cancer Severity With Computational Intelligence In Covid'19 Pandemic

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Dr G Revathy, Dr. A Ramalingam, Mr R Karunamoorthi , Dr.R.Saravanakumar

Abstract

Coronavirus disease 2019 (COVID-19), caused by a newly found strain of the coronavirus family severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has quickly spread around the world, causing a significant public health crisis. As a result, there has been a significant reorganisation of hospital wards and clinical operations around the world to deal with the growing number of COVID-19-positive individuals who require hospitalisation and critical care assistance. Patients with underlying chronic conditions, such as cancer, are particularly concerned about this widespread reallocation of health resources.Lung cancer is a cancer that originates in the lungs. When cells in the body start to grow out of control, cancer develops. As a result, we offer a unique approach in which intracranial pictures are sent to recurrent neural networks to identify cancer stages and the patients' status is classified as safe or non-safe depending on the extent of lung cancer. Because of the rise in Covid, it is no longer safe for a cancer patient, particularly one with lung cancer, to visit the hospital frequently. As a result, when the situation is truly dire as determined by the results, the patient's family and doctor will be informed.Our proposed Random Forest Tree with Recurrent Neural Network will yield a 90% correct outcome.

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