Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of the American College of Radiology 2022-02, Vol.19 (2), p.274-277
Hauptverfasser:	Dreyer, Keith J., Allen, Bibb, Wald, Christoph
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial Intelligence Machine Learning
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page	277
container_issue	2
container_start_page	274
container_title	Journal of the American College of Radiology
container_volume	19
creator	Dreyer, Keith J. Allen, Bibb Wald, Christoph
description
doi_str_mv	10.1016/j.jacr.2021.06.025
format	Article
fullrecord	<record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2579627135</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S154614402100733X</els_id><sourcerecordid>2579627135</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-bcb6a99f6a636491c47823ad4c4f41106f4dd1eecd4f8bba45aa82a1695bb26e3</originalsourceid><addsrcrecordid>eNp9kE1LxDAURYMofv8BF9Klm9YkTdNW3Ayjo8KIMCq6Mrwmr5IhM9GkM-C_t2XUpat3F-deeIeQE0YzRpk8n2dz0CHjlLOMyozyYovss6Ko0lzUr9tDFjJlQtA9chDjnFJellW1S_ZyIRnNudgnbzMEl7744EzyuAprtM7BUmPi22RyNUrHDiGgSUahs63VFlxyt-zQOfuOA3bvDbp4kcygs34JDhNYmmTq323srI5HZKcFF_H45x6S58n10_g2nT7c3I1H01QLSru00Y2Eum4lyFyKmmlRVjwHI7RoBWNUtsIYhqiNaKumAVEAVByYrIum4RLzQ3K22f0I_nOFsVMLGzUOv6BfRcWLspa8ZHnRo3yD6uBjDNiqj2AXEL4Uo2rwquZq8KoGr4pK1XvtS6c_-6tmgeav8iuyBy43QG8D1xaDitoOhowNqDtlvP1v_xuPyImg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2579627135</pqid></control><display><type>article</type><title>Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Dreyer, Keith J. ; Allen, Bibb ; Wald, Christoph</creator><creatorcontrib>Dreyer, Keith J. ; Allen, Bibb ; Wald, Christoph</creatorcontrib><identifier>ISSN: 1546-1440</identifier><identifier>EISSN: 1558-349X</identifier><identifier>DOI: 10.1016/j.jacr.2021.06.025</identifier><identifier>PMID: 34610324</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Artificial Intelligence ; Machine Learning</subject><ispartof>Journal of the American College of Radiology, 2022-02, Vol.19 (2), p.274-277</ispartof><rights>2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-bcb6a99f6a636491c47823ad4c4f41106f4dd1eecd4f8bba45aa82a1695bb26e3</citedby><cites>FETCH-LOGICAL-c400t-bcb6a99f6a636491c47823ad4c4f41106f4dd1eecd4f8bba45aa82a1695bb26e3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jacr.2021.06.025$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34610324$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Dreyer, Keith J.</creatorcontrib><creatorcontrib>Allen, Bibb</creatorcontrib><creatorcontrib>Wald, Christoph</creatorcontrib><title>Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics</title><title>Journal of the American College of Radiology</title><addtitle>J Am Coll Radiol</addtitle><subject>Artificial Intelligence</subject><subject>Machine Learning</subject><issn>1546-1440</issn><issn>1558-349X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kE1LxDAURYMofv8BF9Klm9YkTdNW3Ayjo8KIMCq6Mrwmr5IhM9GkM-C_t2XUpat3F-deeIeQE0YzRpk8n2dz0CHjlLOMyozyYovss6Ko0lzUr9tDFjJlQtA9chDjnFJellW1S_ZyIRnNudgnbzMEl7744EzyuAprtM7BUmPi22RyNUrHDiGgSUahs63VFlxyt-zQOfuOA3bvDbp4kcygs34JDhNYmmTq323srI5HZKcFF_H45x6S58n10_g2nT7c3I1H01QLSru00Y2Eum4lyFyKmmlRVjwHI7RoBWNUtsIYhqiNaKumAVEAVByYrIum4RLzQ3K22f0I_nOFsVMLGzUOv6BfRcWLspa8ZHnRo3yD6uBjDNiqj2AXEL4Uo2rwquZq8KoGr4pK1XvtS6c_-6tmgeav8iuyBy43QG8D1xaDitoOhowNqDtlvP1v_xuPyImg</recordid><startdate>202202</startdate><enddate>202202</enddate><creator>Dreyer, Keith J.</creator><creator>Allen, Bibb</creator><creator>Wald, Christoph</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>202202</creationdate><title>Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics</title><author>Dreyer, Keith J. ; Allen, Bibb ; Wald, Christoph</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-bcb6a99f6a636491c47823ad4c4f41106f4dd1eecd4f8bba45aa82a1695bb26e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial Intelligence</topic><topic>Machine Learning</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dreyer, Keith J.</creatorcontrib><creatorcontrib>Allen, Bibb</creatorcontrib><creatorcontrib>Wald, Christoph</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of the American College of Radiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dreyer, Keith J.</au><au>Allen, Bibb</au><au>Wald, Christoph</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics</atitle><jtitle>Journal of the American College of Radiology</jtitle><addtitle>J Am Coll Radiol</addtitle><date>2022-02</date><risdate>2022</risdate><volume>19</volume><issue>2</issue><spage>274</spage><epage>277</epage><pages>274-277</pages><issn>1546-1440</issn><eissn>1558-349X</eissn><cop>United States</cop><pub>Elsevier Inc</pub><pmid>34610324</pmid><doi>10.1016/j.jacr.2021.06.025</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record>
fulltext	fulltext
identifier	ISSN: 1546-1440
ispartof	Journal of the American College of Radiology, 2022-02, Vol.19 (2), p.274-277
issn	1546-1440 1558-349X
language	eng
recordid	cdi_proquest_miscellaneous_2579627135
source	MEDLINE; Elsevier ScienceDirect Journals Complete
subjects	Artificial Intelligence Machine Learning
title	Real-World Surveillance of FDA-Cleared Artificial Intelligence Models: Rationale and Logistics
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-03T23%3A03%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Real-World%20Surveillance%20of%20FDA-Cleared%20Artificial%20Intelligence%20Models:%20Rationale%20and%20Logistics&rft.jtitle=Journal%20of%20the%20American%20College%20of%20Radiology&rft.au=Dreyer,%20Keith%20J.&rft.date=2022-02&rft.volume=19&rft.issue=2&rft.spage=274&rft.epage=277&rft.pages=274-277&rft.issn=1546-1440&rft.eissn=1558-349X&rft_id=info:doi/10.1016/j.jacr.2021.06.025&rft_dat=%3Cproquest_cross%3E2579627135%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2579627135&rft_id=info:pmid/34610324&rft_els_id=S154614402100733X&rfr_iscdi=true