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	<title>CT enterography &#8211; BIOENGINEER.ORG</title>
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		<title>AI Learns to Grade Crohn&#8217;s Disease Severity From Just a Handful of Expert-Labeled Cases</title>
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		<pubDate>Fri, 09 Oct 2026 07:57:52 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Clinical decision support]]></category>
		<category><![CDATA[Crohn's disease]]></category>
		<category><![CDATA[CT enterography]]></category>
		<category><![CDATA[electronic medical records]]></category>
		<category><![CDATA[few-shot learning]]></category>
		<category><![CDATA[inflammatory bowel disease]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[nested cross-validation]]></category>
		<category><![CDATA[predictive markers]]></category>
		<category><![CDATA[prototypical networks]]></category>
		<category><![CDATA[severity stratification]]></category>
		<category><![CDATA[SHAP interpretability]]></category>
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					<description><![CDATA[Researchers in China built a prototypical network-based few-shot learning framework that reproduces expert consensus severity stratification in newly diagnosed Crohn's disease from small electronic medical record datasets.]]></description>
		
		
		
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