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The ongoing pandemic of coronavirus disease 2019 (COVID-19) is rapidly evolving, thereby posing a profound challenge to the global healthcare system. Cardiometabolic disorders are associated with poor clinical outcomes in persons with COVID-19. Healthcare challenges during the COVID-19 pandemic are linked to resource constraints including shortage of Personal Protective Equipment's (PPE), laboratory tests and medication. In this context, a group of clinical experts discussed the endocrine and cardiology vigilance required in times of CO

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Thus, we demonstrate the potential of rule-based approaches for images which allows to combine advantages of neural networks and rule learning.Since the first case of coronavirus disease 2019 (COVID-19) was discovered in December 2019, COVID-19 swiftly spread over the world. By the end of March 2021, more than 136 million patients have been infected. Since the second and third waves of the COVID-19 outbreak are in full swing, investigating effective and timely solutions for patients' check-ups and treatment is important. Although th