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10.1007/s00138-020-01101-5 http://scihub22266oqcxt.onion/10.1007/s00138-020-01101-5 32834523!7386599!32834523     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Mach+Vis+Appl 2020 ; 31 (6): 53 Nephropedia Template TP {{tp|p=32834523|t=2020. Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19 |pdf=|usr=}}{{32834523}} gab.com Text Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19 JO: Mach Vis Appl http://www.kidney.de/pget.php?&tw=1&pmid=32834523 #FOAvip Shortly after deep learning algorithms were applied to Image Analysis, and more importantly to medical imaging, their applications increased significantly to become a trend. Likewise, deep learning applications (DL) on pulmonary medical images emerged to achieve remarkable advances leading to promising clinical trials. Yet, coronavirus can be the real trigger to open the route for fast integration of DL in hospitals and medical centers. This paper reviews the development of deep learning applications in medical image analysis targeting pulmonary imaging and giving insights of contributions to COVID-19. It covers more than 160 contributions and surveys in this field, all issued between February 2017 and May 2020 inclusively, highlighting various deep learning tasks such as classification, segmentation, and detection, as well as different pulmonary pathologies like airway diseases, lung cancer, COVID-19 and other infections. It summarizes and discusses the current state-of-the-art approaches in this research domain, highlighting the challenges, especially with COVID-19 pandemic current situation. Twit Text FOAVip Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19 ????Mach Vis Appl http://www.kidney.de/pget.php?&tw=1&pmid=32834523 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32834523 #FOAvip English Wikipedia <ref>{{Cite pmid|32834523}}</ref> Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19 #MMPMID32834523 Farhat H; Sakr GE; Kilany R Mach Vis Appl 2020[]; 31 (6): 53 PMID32834523show ga Shortly after deep learning algorithms were applied to Image Analysis, and more importantly to medical imaging, their applications increased significantly to become a trend. Likewise, deep learning applications (DL) on pulmonary medical images emerged to achieve remarkable advances leading to promising clinical trials. Yet, coronavirus can be the real trigger to open the route for fast integration of DL in hospitals and medical centers. This paper reviews the development of deep learning applications in medical image analysis targeting pulmonary imaging and giving insights of contributions to COVID-19. It covers more than 160 contributions and surveys in this field, all issued between February 2017 and May 2020 inclusively, highlighting various deep learning tasks such as classification, segmentation, and detection, as well as different pulmonary pathologies like airway diseases, lung cancer, COVID-19 and other infections. It summarizes and discusses the current state-of-the-art approaches in this research domain, highlighting the challenges, especially with COVID-19 pandemic current situation. äDeep learning applications in pulmonary medical imaging: recent update(epmc).pdf DeepDyve Pubget Overpricing