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10.1007/s12553-021-00520-2 http://scihub22266oqcxt.onion/10.1007/s12553-021-00520-2 33585153!7864619!33585153     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33585153&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Health+Technol+(Berl) 2021 ; 11 (2): 411-424 Nephropedia Template TP {{tp|p=33585153|t=2021. Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging |pdf=|usr=}}{{33585153}} gab.com Text Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging JO: Health Technol (Berl) http://www.kidney.de/pget.php?&tw=1&pmid=33585153 #FOAvip The scientific community has joined forces to mitigate the scope of the current COVID-19 pandemic. The early identification of the disease, as well as the evaluation of its evolution is a primary task for the timely application of medical protocols. The use of medical images of the chest provides valuable information to specialists. Specifically, chest X-ray images have been the focus of many investigations that apply artificial intelligence techniques for the automatic classification of this disease. The results achieved to date on the subject are promising. However, some results of these investigations contain errors that must be corrected to obtain appropriate models for clinical use. This research discusses some of the problems found in the current scientific literature on the application of artificial intelligence techniques in the automatic classification of COVID-19. It is evident that in most of the reviewed works an incorrect evaluation protocol is applied, which leads to overestimating the results. Twit Text FOAVip Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging ????Health Technol (Berl) http://www.kidney.de/pget.php?&tw=1&pmid=33585153 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33585153 #FOAvip English Wikipedia <ref>{{Cite pmid|33585153}}</ref> Current limitations to identify COVID-19 using artificial intelligence with chest X-ray imaging #MMPMID33585153 Lopez-Cabrera JD; Orozco-Morales R; Portal-Diaz JA; Lovelle-Enriquez O; Perez-Diaz M Health Technol (Berl) 2021[]; 11 (2): 411-424 PMID33585153show ga The scientific community has joined forces to mitigate the scope of the current COVID-19 pandemic. The early identification of the disease, as well as the evaluation of its evolution is a primary task for the timely application of medical protocols. The use of medical images of the chest provides valuable information to specialists. Specifically, chest X-ray images have been the focus of many investigations that apply artificial intelligence techniques for the automatic classification of this disease. The results achieved to date on the subject are promising. However, some results of these investigations contain errors that must be corrected to obtain appropriate models for clinical use. This research discusses some of the problems found in the current scientific literature on the application of artificial intelligence techniques in the automatic classification of COVID-19. It is evident that in most of the reviewed works an incorrect evaluation protocol is applied, which leads to overestimating the results. äCurrent limitations to identify COVID-19 using artificial intelligence(epmc).pdf DeepDyve Pubget Overpricing