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<meta name="DC.Language" content="en" />
<meta name="DC.Title" content="Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial" />
<meta name="DC.Identifier" content="10.3174/ajnr.A8387" />
<meta name="DC.Date" content="2024-11-01" />
<meta name="DC.Publisher" content="American Journal of Neuroradiology" />
<meta name="DC.Rights" content="© 2024 by American Journal of Neuroradiology" />
<meta name="DC.AccessRights" content="restricted" />
<meta name="DC.Description" content="BACKGROUND AND PURPOSE: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.

MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. Medical students and resident trainees were asked to identify intracranial hemorrhage and large-vessel occlusion in 100 noncontrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating artificial intelligence for intracranial hemorrhage only ( n = 26); the other, for large-vessel occlusion only ( n = 28). Primary outcomes included accuracy, sensitivity, and specificity for intracranial hemorrhage/large-vessel occlusion detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with the t test; differences in continuous variables were assessed with ANOVA.

RESULTS: Forty-eight participants completed the study, generating 10,779 intracranial hemorrhage or large-vessel occlusion interpretations. With diagnostic aid, medical student accuracy improved 11.0 points ( P &lt; .001) and resident trainee accuracy showed no significant change. Intracranial hemorrhage interpretation time increased with diagnostic aid for both groups ( P &lt; .001), while large-vessel occlusion interpretation time decreased for medical students ( P &lt; .001). Despite worse performance in the detection of the smallest-versus-largest hemorrhages at baseline, medical students were not more likely to accept a true-positive artificial intelligence result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the artificial intelligence or when supplied with an incorrect artificial intelligence result.

CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with artificial intelligence for medical students compared with resident trainees. However, medical students were less likely than resident trainees to overrule incorrect artificial intelligence interpretations and were less accurate, even with diagnostic aid, than the artificial intelligence was by itself.

AI
:   artificial intelligence
ICH
:   intracranial hemorrhage
LVO
:   large-vessel occlusion
MS
:   medical students
RT
:   resident trainees" />
<meta name="DC.Contributor" content="David A. Fussell" />
<meta name="DC.Contributor" content="Cynthia C. Tang" />
<meta name="DC.Contributor" content="Jake Sternhagen" />
<meta name="DC.Contributor" content="Varun V. Marrey" />
<meta name="DC.Contributor" content="Kelsey M. Roman" />
<meta name="DC.Contributor" content="Jeremy Johnson" />
<meta name="DC.Contributor" content="Michael J. Head" />
<meta name="DC.Contributor" content="Hayden R. Troutt" />
<meta name="DC.Contributor" content="Charles H. Li" />
<meta name="DC.Contributor" content="Peter D. Chang" />
<meta name="DC.Contributor" content="John Joseph" />
<meta name="DC.Contributor" content="Daniel S. Chow" />
<meta name="article:published_time" content="2024-11-01" />
<meta name="article:section" content="Artificial Intelligence" />
<meta name="citation_title" content="Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial" />
<meta name="citation_abstract" lang="en" content="&lt;h3&gt;BACKGROUND AND PURPOSE:&lt;/h3&gt;
&lt;p&gt;Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.&lt;/p&gt;&lt;h3&gt;MATERIALS AND METHODS:&lt;/h3&gt;
&lt;p&gt;This prospective study was conducted between March 2023 and October 2023. Medical students and resident trainees were asked to identify intracranial hemorrhage and large-vessel occlusion in 100 noncontrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating artificial intelligence for intracranial hemorrhage only (&lt;i&gt;n&lt;/i&gt; = 26); the other, for large-vessel occlusion only (&lt;i&gt;n&lt;/i&gt; = 28). Primary outcomes included accuracy, sensitivity, and specificity for intracranial hemorrhage/large-vessel occlusion detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with the &lt;i&gt;t&lt;/i&gt; test; differences in continuous variables were assessed with ANOVA.&lt;/p&gt;&lt;h3&gt;RESULTS:&lt;/h3&gt;
&lt;p&gt;Forty-eight participants completed the study, generating 10,779 intracranial hemorrhage or large-vessel occlusion interpretations. With diagnostic aid, medical student accuracy improved 11.0 points (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001) and resident trainee accuracy showed no significant change. Intracranial hemorrhage interpretation time increased with diagnostic aid for both groups (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001), while large-vessel occlusion interpretation time decreased for medical students (&lt;i&gt;P&lt;/i&gt; &amp;lt; .001). Despite worse performance in the detection of the smallest-versus-largest hemorrhages at baseline, medical students were not more likely to accept a true-positive artificial intelligence result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the artificial intelligence or when supplied with an incorrect artificial intelligence result.&lt;/p&gt;&lt;h3&gt;CONCLUSIONS:&lt;/h3&gt;
&lt;p&gt;This study demonstrated greater improvement in diagnostic accuracy with artificial intelligence for medical students compared with resident trainees. However, medical students were less likely than resident trainees to overrule incorrect artificial intelligence interpretations and were less accurate, even with diagnostic aid, than the artificial intelligence was by itself.&lt;/p&gt;" />
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<meta name="twitter:title" content="Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial" />
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<meta name="twitter:description" content="BACKGROUND AND PURPOSE: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.

MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. Medical students and resident trainees were asked to identify intracranial hemorrhage and large-vessel occlusion in 100 noncontrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating artificial intelligence for intracranial hemorrhage only ( n = 26); the other, for large-vessel occlusion only ( n = 28). Primary outcomes included accuracy, sensitivity, and specificity for intracranial hemorrhage/large-vessel occlusion detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with the t test; differences in continuous variables were assessed with ANOVA.

RESULTS: Forty-eight participants completed the study, generating 10,779 intracranial hemorrhage or large-vessel occlusion interpretations. With diagnostic aid, medical student accuracy improved 11.0 points ( P &lt; .001) and resident trainee accuracy showed no significant change. Intracranial hemorrhage interpretation time increased with diagnostic aid for both groups ( P &lt; .001), while large-vessel occlusion interpretation time decreased for medical students ( P &lt; .001). Despite worse performance in the detection of the smallest-versus-largest hemorrhages at baseline, medical students were not more likely to accept a true-positive artificial intelligence result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the artificial intelligence or when supplied with an incorrect artificial intelligence result.

CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with artificial intelligence for medical students compared with resident trainees. However, medical students were less likely than resident trainees to overrule incorrect artificial intelligence interpretations and were less accurate, even with diagnostic aid, than the artificial intelligence was by itself.

AI
:   artificial intelligence
ICH
:   intracranial hemorrhage
LVO
:   large-vessel occlusion
MS
:   medical students
RT
:   resident trainees" />
<meta name="og-title" property="og:title" content="Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial" />
<meta name="og-url" property="og:url" content="http://ajnr-stage2.stage.highwire.org/content/45/11/1647" />
<meta name="og-site-name" property="og:site_name" content="American Journal of Neuroradiology" />
<meta name="og-description" property="og:description" content="BACKGROUND AND PURPOSE: Recently, artificial intelligence tools have been deployed with increasing speed in educational and clinical settings. However, the use of artificial intelligence by trainees across different levels of experience has not been well-studied. This study investigates the impact of artificial intelligence assistance on the diagnostic accuracy for intracranial hemorrhage and large-vessel occlusion by medical students and resident trainees.

MATERIALS AND METHODS: This prospective study was conducted between March 2023 and October 2023. Medical students and resident trainees were asked to identify intracranial hemorrhage and large-vessel occlusion in 100 noncontrast head CTs and 100 head CTAs, respectively. One group received diagnostic aid simulating artificial intelligence for intracranial hemorrhage only ( n = 26); the other, for large-vessel occlusion only ( n = 28). Primary outcomes included accuracy, sensitivity, and specificity for intracranial hemorrhage/large-vessel occlusion detection without and with aid. Study interpretation time was a secondary outcome. Individual responses were pooled and analyzed with the t test; differences in continuous variables were assessed with ANOVA.

RESULTS: Forty-eight participants completed the study, generating 10,779 intracranial hemorrhage or large-vessel occlusion interpretations. With diagnostic aid, medical student accuracy improved 11.0 points ( P &lt; .001) and resident trainee accuracy showed no significant change. Intracranial hemorrhage interpretation time increased with diagnostic aid for both groups ( P &lt; .001), while large-vessel occlusion interpretation time decreased for medical students ( P &lt; .001). Despite worse performance in the detection of the smallest-versus-largest hemorrhages at baseline, medical students were not more likely to accept a true-positive artificial intelligence result for these more difficult tasks. Both groups were considerably less accurate when disagreeing with the artificial intelligence or when supplied with an incorrect artificial intelligence result.

CONCLUSIONS: This study demonstrated greater improvement in diagnostic accuracy with artificial intelligence for medical students compared with resident trainees. However, medical students were less likely than resident trainees to overrule incorrect artificial intelligence interpretations and were less accurate, even with diagnostic aid, than the artificial intelligence was by itself.

AI
:   artificial intelligence
ICH
:   intracranial hemorrhage
LVO
:   large-vessel occlusion
MS
:   medical students
RT
:   resident trainees" />
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    <div class="highwire-article-citation highwire-citation-type-highwire-article node111446--5" data-node-nid="111446" id="top-node-111446--6364298942" data-pisa="ajnr;45/11/1647" data-pisa-master="ajnr;ajnr.A8387" data-apath="/ajnr/45/11/1647.atom" data-hw-author-tooltip-instance="highwire_author_tooltip"><div class="highwire-cite highwire-cite-highwire-article highwire-citation-jcore-article-title-complete clearfix has-author-tooltip highwire-citation-highwire-article-top-a">
  
  
      <div class="highwire-cite-overline"><span  class="highwire-cite-metadata-article-type highwire-cite-metadata">Research Article</span><span class="separator-pipe"></span><span  class="highwire-cite-metadata-art-cat highwire-cite-metadata"><span class="wrapper">Artificial Intelligence</span></span></div>
  
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      <h1 class="highwire-cite-title" id="page-title">Artificial Intelligence Efficacy as a Function of Trainee Interpreter Proficiency: Lessons from a Randomized Controlled Trial</h1>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0">David A. Fussell</span>, <span class="highwire-citation-author" data-delta="1">Cynthia C. Tang</span>, <span class="highwire-citation-author" data-delta="2">Jake Sternhagen</span>, <span class="highwire-citation-author" data-delta="3">Varun V. Marrey</span>, <span class="highwire-citation-author" data-delta="4">Kelsey M. Roman</span>, <span class="highwire-citation-author" data-delta="5">Jeremy Johnson</span>, <span class="highwire-citation-author" data-delta="6">Michael J. Head</span>, <span class="highwire-citation-author" data-delta="7">Hayden R. Troutt</span>, <span class="highwire-citation-author" data-delta="8">Charles H. Li</span>, <span class="highwire-citation-author" data-delta="9">Peter D. Chang</span>, <span class="highwire-citation-author" data-delta="10">John Joseph</span> and <span class="highwire-citation-author" data-delta="11">Daniel S. Chow</span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">November 2024,  </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">45 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(11) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1647-1654; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata">DOI: https://doi.org/10.3174/ajnr.A8387 </span></div>
  
  
  
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<div id="hw-article-author-popups-top-node-111446--6364298942" style="display: none;"><div class="author-tooltip-0"><div class="author-tooltip-name">David A. Fussell </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiological Sciences (D.A.F., C.C.T., J.S., V.V.M., J.J., H.R.T., C.H.L., P.D.C., D.S.C.), University of California, Irvine, Irvine, California</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=David%2BA.%2BFussell%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Fussell%20DA&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3ADavid%2BA.%2BFussell%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0009-0003-0833-9148" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for David A. 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Tang </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiological Sciences (D.A.F., C.C.T., J.S., V.V.M., J.J., H.R.T., C.H.L., P.D.C., D.S.C.), University of California, Irvine, Irvine, California</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=Cynthia%2BC.%2BTang%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Tang%20CC&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link last"><a href="/search/author1%3ACynthia%2BC.%2BTang%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li></ul></div><div class="author-tooltip-2"><div class="author-tooltip-name">Jake Sternhagen </div><div class="author-tooltip-affiliation"><span class="author-tooltip-text"><div class='author-affiliation'><span class='nlm-sup'>a</span>From the Department of Radiological Sciences (D.A.F., C.C.T., J.S., V.V.M., J.J., H.R.T., C.H.L., P.D.C., D.S.C.), University of California, Irvine, Irvine, California</div></span></div><ul class="author-tooltip-find-more"><li class="author-tooltip-gs-link first"><a href="/lookup/google-scholar?link_type=googlescholar&amp;gs_type=author&amp;author%5B0%5D=Jake%2BSternhagen%2B" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on Google Scholar</a></li><li class="author-tooltip-pubmed-link"><a href="/lookup/external-ref?access_num=Sternhagen%20J&amp;link_type=AUTHORSEARCH" target="_blank" class="" data-icon-position="" data-hide-link-title="0">Find this author on PubMed</a></li><li class="author-site-search-link"><a href="/search/author1%3AJake%2BSternhagen%2B" rel="nofollow" class="" data-icon-position="" data-hide-link-title="0">Search for this author on this site</a></li><li class="author-orcid-link last"><a href="https://orcid.org/0009-0004-3006-6550" target="_blank" class="" data-icon-position="" data-hide-link-title="0">ORCID record for Jake Sternhagen</a></li></ul></div><div class="author-tooltip-3"><div class="author-tooltip-name">Varun V. 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        	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-volume highwire-cite-metadata">Vol. 45</span>, <span  class="highwire-cite-metadata-issue highwire-cite-metadata">Issue 11 </span><div  class="highwire-cite-metadata-pubdate highwire-cite-metadata">1 Nov 2024 </div></div>
      
      
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    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Nov 2024, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">45 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(11) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1647-1654; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A8387 </span></div>
  
  
  
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      <div class="highwire-cite-title">AI Efficacy Based on Trainee Proficiency</div>  
    	<div class="highwire-cite-authors"><span  class="highwire-citation-authors"><span class="highwire-citation-author first" data-delta="0"><span class="nlm-given-names">David A.</span> <span class="nlm-surname">Fussell</span></span>, <span class="highwire-citation-author" data-delta="1"><span class="nlm-given-names">Cynthia C.</span> <span class="nlm-surname">Tang</span></span>, <span class="highwire-citation-author" data-delta="2"><span class="nlm-given-names">Jake</span> <span class="nlm-surname">Sternhagen</span></span>, <span class="highwire-citation-author" data-delta="3"><span class="nlm-given-names">Varun V.</span> <span class="nlm-surname">Marrey</span></span>, <span class="highwire-citation-author" data-delta="4"><span class="nlm-given-names">Kelsey M.</span> <span class="nlm-surname">Roman</span></span>, <span class="highwire-citation-author" data-delta="5"><span class="nlm-given-names">Jeremy</span> <span class="nlm-surname">Johnson</span></span>, <span class="highwire-citation-author" data-delta="6"><span class="nlm-given-names">Michael J.</span> <span class="nlm-surname">Head</span></span>, <span class="highwire-citation-author" data-delta="7"><span class="nlm-given-names">Hayden R.</span> <span class="nlm-surname">Troutt</span></span>, <span class="highwire-citation-author" data-delta="8"><span class="nlm-given-names">Charles H.</span> <span class="nlm-surname">Li</span></span>, <span class="highwire-citation-author" data-delta="9"><span class="nlm-given-names">Peter D.</span> <span class="nlm-surname">Chang</span></span>, <span class="highwire-citation-author" data-delta="10"><span class="nlm-given-names">John</span> <span class="nlm-surname">Joseph</span></span>, <span class="highwire-citation-author" data-delta="11"><span class="nlm-given-names">Daniel S.</span> <span class="nlm-surname">Chow</span></span></span></div>
  
    	<div class="highwire-cite-metadata"><span  class="highwire-cite-metadata-journal highwire-cite-metadata">American Journal of Neuroradiology </span><span  class="highwire-cite-metadata-date highwire-cite-metadata">Nov 2024, </span><span  class="highwire-cite-metadata-volume highwire-cite-metadata">45 </span><span  class="highwire-cite-metadata-issue highwire-cite-metadata">(11) </span><span  class="highwire-cite-metadata-pages highwire-cite-metadata">1647-1654; </span><span  class="highwire-cite-metadata-doi highwire-cite-metadata"><span class="label">DOI:</span> 10.3174/ajnr.A8387 </span></div>
  
  
  
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