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	<title>multi-scale fusion &#8211; BIOENGINEER.ORG</title>
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		<title>Lightweight AI Reads Brain Tumor Scans and Knows When It Is Unsure</title>
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		<pubDate>Wed, 14 Oct 2026 17:31:07 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Attention Mechanisms]]></category>
		<category><![CDATA[brain tumor]]></category>
		<category><![CDATA[cross-dataset validation]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[EfficientNet]]></category>
		<category><![CDATA[evidential deep learning]]></category>
		<category><![CDATA[interpretable AI]]></category>
		<category><![CDATA[lightweight neural network]]></category>
		<category><![CDATA[Medical imaging AI]]></category>
		<category><![CDATA[MRI]]></category>
		<category><![CDATA[multi-scale fusion]]></category>
		<category><![CDATA[uncertainty quantification]]></category>
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					<description><![CDATA[Researchers have built a 10.97-million-parameter neural network that classifies brain tumors on MRI with 99.2 percent accuracy while quantifying its own uncertainty in a single pass.]]></description>
		
		
		
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