LEADER 04112nam 2200913z- 450 001 9910619470303321 005 20221025 010 $a3-0365-5390-8 035 $a(CKB)5670000000391571 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/93224 035 $a(oapen)doab93224 035 $a(EXLCZ)995670000000391571 100 $a20202210d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aUpdates in Management of SARS-CoV-2 Infection 210 $cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (198 p.) 311 08$a3-0365-5389-4 330 $aSevere acute respiratory syndrome coronavirus 2 (SARS?CoV?2) has spread worldwide from the beginning of 2020. The infection is mostly asymptomatic but some patients may develop COVID?19 (coronavirus disease 2019) with a severe or critical course leading to pneumonia, acute respiratory distress syndrome, and multiorgan failure. Apart from the virus?related damage of the lungs, pathomechanism of the disease seems to be linked to thromboembolism and inflammation accompanied by overproduction of proinflammatory cytokines, termed a cytokine storm, responsible for multiorgan damage and death. Since the development of a new therapeutic molecule, dedicated strictly to a particular virus is time?consuming, physicians and scientists have started to test and repurpose old medications. Unfortunately, after one year of pandemics, there is still a lack of optimal therapy and no clear indicators of recovery. A major issue is also insufficient knowledge on predictors of the severe or deadly course of the disease, which could also help to switch from one therapeutic option to another. Due to many gaps still existing in the management of COVID-19, there is a need for the accumulation of new data particularly from real-world experience, which could be applicable to practice guidelines. The objective of this special issue of the Journal of Clinical Medicine is to provide an update on the mangement for the diagnostic workup and pharmacotherapy of SARS?CoV?2 infection. 606 $aMedicine$2bicssc 610 $aangiotensin 1 receptor (AT1R) 610 $aangiotensin II 610 $aantigen detection 610 $aartificial intelligence 610 $aAT1R concentration 610 $aCharlson Comorbidities Index 610 $achildren 610 $aclinical outcome 610 $aclinical presentation 610 $acluster analysis 610 $aco-infections 610 $acoronavirus disease 2019 610 $acoronavirus disease 2019 (COVID-19) 610 $aCOVID-19 610 $aCOVID-19 diagnosis 610 $aCOVID-19 pneumonia 610 $acritical care 610 $acytokines 610 $aCytomegalovirus 610 $adiagnosis 610 $aepidemiology 610 $aindividualized management 610 $ainflammation 610 $ainterleukin-6 610 $akidney failure 610 $aliver functional tests 610 $aliver markers 610 $alongitudinal cluster 610 $amedical imaging 610 $ameta-analysis 610 $amethodological credibility 610 $amorbidity 610 $amortality 610 $an/a 610 $apandemic 610 $aPCR test 610 $apersonalized medicine 610 $aprognosis 610 $arapid diagnostic test 610 $aSARS-CoV-2 610 $asevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 610 $aseverity 610 $asymptomatology 610 $asymptoms' severity 610 $asystematic umbrella review 610 $atherapy 610 $atocilizumab 610 $atrial sequential analysis 615 7$aMedicine 700 $aFlisiak$b Robert$4edt$01328782 702 $aFlisiak$b Robert$4oth 906 $aBOOK 912 $a9910619470303321 996 $aUpdates in Management of SARS-CoV-2 Infection$93038948 997 $aUNINA LEADER 03934nam 22006495 450 001 9910911294303321 005 20251113202342.0 010 $a9783031714269 010 $a3031714261 024 7 $a10.1007/978-3-031-71426-9 035 $a(MiAaPQ)EBC31804420 035 $a(Au-PeEL)EBL31804420 035 $a(CKB)36676811000041 035 $a(OCoLC)1474242101 035 $a(DE-He213)978-3-031-71426-9 035 $a(EXLCZ)9936676811000041 100 $a20241125d2024 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence and Its Practical Applications in the Digital Economy $eProceedings of the International Conference on Artificial Intelligence and Its Practical Applications in the Age of Digital Transformation 2024, Volume 1 /$fedited by Yahya Mohamed Elhadj, Mohamedade Farouk Nanne, Anis Koubaa, Farid Meziane, Mohamed Deriche 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (284 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v861 311 08$a9783031714252 311 08$a3031714253 327 $aThe prediction of the wind speed and the solar irradiation in the Sahel using the Artificial neural networks case study site of Nouakchott -- Deep learning for smart grid application addressing data scarcity challenges and enhancing load forecasting efficiency -- Enhancing Advanced Time-Series Forecasting of Electric Energy Consumption based on RNN augmented with LSTM Techniques. 330 $aArtificial Intelligence (AI) technologies hold immense promise for developing countries by offering innovative solutions to longstanding challenges. By leveraging AI in health care, education, economic development, infrastructure, and resource management, these countries can potentially leapfrog traditional development stages and improve the quality of life for their populations. However, it's essential to approach AI deployment with ethical considerations to ensure that the technology serves the best interests of these communities and thus to maximize the expected benefits. The I2COMSAPP'24 "International Conference on Artificial Intelligence and its Applications in the Age of Digital Transformation" aims to provide an excellent opportunity to gather experts, researchers, practitioners, and innovators from various fields to explore the latest advancements, challenges, and practical implementations of artificial intelligence and machine learning (ML) technologies. Moreover, it aims to foster knowledge sharing, collaboration, and networking among professionals who are driving responsible and innovative use of AI and leveraging real-world applications for the betterment of society and industries. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v861 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aEconomic history 606 $aComputational Intelligence 606 $aArtificial Intelligence 606 $aEconomy-wide Country Studies 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 0$aEconomic history. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 615 24$aEconomy-wide Country Studies. 676 $a658.0563 700 $aElhadj$b Yahya Mohamed$01776573 701 $aNanne$b Mohamedade Farouk$01776574 701 $aKouba?a$b Anis$00 701 $aMeziane$b Farid$01776575 701 $aDeriche$b M$g(Mohamed)$01232009 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910911294303321 996 $aArtificial Intelligence and Its Practical Applications in the Digital Economy$94525583 997 $aUNINA