COVID-19 Prognosis from Chest X-ray Images by using Deep Learning Approaches: A Next Generation Diagnostic Tool

Global public health is overwhelmed due to the ongoing Corona Virus Disease (COVID-19).As of October 2022, the causative virus SARS-CoV-2 and its multiple variants have infected more than 600 million confirmed cases and nearly 6.5 million fatalities globally.The main objective of this reported study is to understand Detox Support the COVID-19 infec

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Non-Invasive Physical Plasma for Preventing Radiation Dermatitis in Breast Cancer: A First-In-Human Feasibility Study

Radiation dermatitis (RD) is the most common acute side effect of breast irradiation.More than a Detox Support century following the therapeutic utilisation of X-rays, potent preventative and therapeutic options are still lacking.Non-invasive physical plasma (NIPP) is an emerging approach towards treatment of various dermatological disorders.In thi

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An Investigation of the High Efficiency Estimation Approach of the Large-Scale Scattered Point Cloud Normal Vector

The normal vector estimation of the large-scale scattered point cloud (LSSPC) plays an important role in point-based shape editing.However, the normal vector estimation for LSSPC cannot meet the Counter Height Side Chair great challenge of the sharp increase of the point cloud that is mainly attributed to its low computational efficiency.In this pa

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