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	<title>2D/3D medical data integration &#8211; BIOENGINEER.ORG</title>
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	<title>2D/3D medical data integration &#8211; BIOENGINEER.ORG</title>
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		<title>Building Generalist Radiology Models with Massive 2D/3D Data</title>
		<link>https://bioengineer.org/building-generalist-radiology-models-with-massive-2d-3d-data/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sat, 23 Aug 2025 22:30:00 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[2D/3D medical data integration]]></category>
		<category><![CDATA[AI in medical imaging]]></category>
		<category><![CDATA[generalist radiology models]]></category>
		<category><![CDATA[multi-modal learning in radiology]]></category>
		<category><![CDATA[web-scale healthcare datasets]]></category>
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					<description><![CDATA[In an era where artificial intelligence continues to revolutionize medicine, a groundbreaking development is reshaping the landscape of radiology. Researchers led by Wu, Zhang, and Zhang unveil a pioneering approach to constructing a generalist foundation model that seamlessly integrates both two-dimensional (2D) and three-dimensional (3D) medical imaging data on an unprecedented scale. This model is [&#8230;]]]></description>
		
		
		
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