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10.1093/jamia/ocaa210 http://scihub22266oqcxt.onion/10.1093/jamia/ocaa210 32805004!7454645!32805004     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=32805004&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       J+Am+Med+Inform+Assoc 2021 ; 28 (1): 190-192 Nephropedia Template TP {{tp|p=32805004|t=2021. Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 |pdf=|usr=}}{{32805004}} gab.com Text Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 JO: J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=32805004 #FOAvip The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease, resulting in the rapid dissemination of underdeveloped and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks for a shared COVID-19 data source to address the challenges of bias in AI during this pandemic. There is hope that AI can help guide treatment decisions within this crisis; yet given the pervasiveness of biases, a failure to proactively develop comprehensive mitigation strategies during the COVID-19 pandemic risks exacerbating existing health disparities. Twit Text FOAVip Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 ????J Am Med Inform Assoc http://www.kidney.de/pget.php?&tw=1&pmid=32805004 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32805004 #FOAvip English Wikipedia <ref>{{Cite pmid|32805004}}</ref> Bias at warp speed: how AI may contribute to the disparities gap in the time of COVID-19 #MMPMID32805004 Roosli E; Rice B; Hernandez-Boussard T J Am Med Inform Assoc 2021[Jan]; 28 (1): 190-192 PMID32805004show ga The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe artificial intelligence (AI) is a solution to guide clinical decision-making for this novel disease, resulting in the rapid dissemination of underdeveloped and potentially biased models, which may exacerbate the disparities gap. We believe there is an urgent need to enforce the systematic use of reporting standards and develop regulatory frameworks for a shared COVID-19 data source to address the challenges of bias in AI during this pandemic. There is hope that AI can help guide treatment decisions within this crisis; yet given the pervasiveness of biases, a failure to proactively develop comprehensive mitigation strategies during the COVID-19 pandemic risks exacerbating existing health disparities. |*Artificial Intelligence[MESH] |*COVID-19[MESH] |Bias[MESH] |Clinical Decision-Making[MESH] |Health Status Disparities[MESH] |Healthcare Disparities/*ethnology[MESH] |Humans[MESH] |Information Storage and Retrieval/standards[MESH] |Minority Groups[MESH] |Resource Allocation/*methods[MESH]Bias at warp speed: how AI may contribute to the disparities gap in th(epmc).pdf DeepDyve Pubget Overpricing