Titlebook: Computational Intelligence for COVID-19 and Future Pandemics; Emerging Application Utku Kose,Junzo Watada,Jose Antonio Marmolejo Sauc Book

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Biologische Grundlagen der Strahlentherapie,ountry with a remarkable impact on the health of the people, economics, social life, and education setups at the society and country levels. Due to the increase in the cases of COVID-19 at the national and international levels, there is a need for innovative ways in initial screen out and final diag

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https://doi.org/10.1007/978-3-642-96542-5he weak immune and the chronically ill people. Until now scientists could not determine the behavior of the virus to fight it and limit its reproduction and spread among humans. This steady increase in infected and dead people has exhausted the medical staff and led to the collapse of health sectors

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Strahlentherapie atmungsbewegter Tumoreno build an efficient and easy diagnostic framework for COVID-19, artificial intelligence has revealed significant success in several activities, from image processing to natural language processing, particularly with the advent of deep learning (DL). The medical profession requires a high degree of

Nebulizer

https://doi.org/10.1007/978-3-658-01146-8 in the world. The study of Daily Cumulative Rank for each observed country and territory is evaluated. It defines the daily number of average cases from the day of reporting till the day of the study carried out. The study also highlights the impact of the disease on six regions including Africa, A

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https://doi.org/10.1007/978-3-642-94751-3 work, the model of AHP and Grand Prix will be used to select the best neonatal ventilator among seven options of neonatal ventilators; to achieve this, different variables will be analyzed that will help us determine which is the best ventilator according to the criterion taken. When using both mul

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Arbeitszeitaufwand und Leistungen, deal with a significant number of patients requiring medical expertise and achieve accurate and rapid diagnosis and treatment. However, in epidemics, many of these computational intelligence-based diagnosis systems require up-to-date trained machine learning models, which are dependent on receiving