<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>AI in radiology &#8211; BIOENGINEER.ORG</title>
	<atom:link href="https://bioengineer.org/tag/ai-in-radiology/feed/" rel="self" type="application/rss+xml" />
	<link>https://bioengineer.org</link>
	<description>Bioengineering</description>
	<lastBuildDate>Sun, 23 Nov 2025 10:41:56 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.0</generator>

<image>
	<url>https://bioengineer.org/wp-content/uploads/2019/09/cropped-bioengineering-32x32.png</url>
	<title>AI in radiology &#8211; BIOENGINEER.ORG</title>
	<link>https://bioengineer.org</link>
	<width>32</width>
	<height>32</height>
</image> 
<site xmlns="com-wordpress:feed-additions:1">72741379</site>	<item>
		<title>Automated MRI System Revolutionizes Prostate Cancer Detection</title>
		<link>https://bioengineer.org/automated-mri-system-revolutionizes-prostate-cancer-detection/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sun, 23 Nov 2025 10:41:54 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[AI in radiology]]></category>
		<category><![CDATA[Automated MRI system]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[Precision Medicine]]></category>
		<category><![CDATA[Prostate cancer detection]]></category>
		<guid isPermaLink="false">https://bioengineer.org/automated-mri-system-revolutionizes-prostate-cancer-detection/</guid>

					<description><![CDATA[In an era where artificial intelligence is rapidly revolutionizing medical diagnostics, a groundbreaking study has emerged from a team of researchers led by Wu, Liu, and Yang, promising to redefine prostate cancer detection. Published recently in Nature Communications, their work introduces an automated MRI system explicitly designed for the reliable identification of clinically significant prostate [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">300217</post-id>	</item>
		<item>
		<title>Revolutionary AI Enhances Radiology with Unprecedented Speed and Precision</title>
		<link>https://bioengineer.org/revolutionary-ai-enhances-radiology-with-unprecedented-speed-and-precision/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Thu, 05 Jun 2025 16:15:46 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[AI in radiology]]></category>
		<category><![CDATA[Generative AI in healthcare]]></category>
		<category><![CDATA[Medical Imaging Innovation]]></category>
		<category><![CDATA[Radiologist Shortage Solutions]]></category>
		<category><![CDATA[Radiology Efficiency]]></category>
		<guid isPermaLink="false">https://bioengineer.org/revolutionary-ai-enhances-radiology-with-unprecedented-speed-and-precision/</guid>

					<description><![CDATA[A groundbreaking advancement in radiology has emerged from Northwestern Medicine, which is unveiling a pioneering generative AI system. This revolutionary tool is not merely a theoretical construct; it has been meticulously developed in-house and is now proving its capabilities in real clinical settings. This unprecedented initiative promises to significantly enhance productivity in radiology, ensure rapid [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">248491</post-id>	</item>
		<item>
		<title>CNN Automates CT Scoring for Sinus Imaging</title>
		<link>https://bioengineer.org/cnn-automates-ct-scoring-for-sinus-imaging/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sun, 27 Apr 2025 20:59:54 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[AI in radiology]]></category>
		<category><![CDATA[chronic rhinosinusitis]]></category>
		<category><![CDATA[convolutional neural networks]]></category>
		<category><![CDATA[CT scan automation]]></category>
		<category><![CDATA[Lund-Mackay scoring]]></category>
		<guid isPermaLink="false">https://bioengineer.org/cnn-automates-ct-scoring-for-sinus-imaging/</guid>

					<description><![CDATA[In a groundbreaking advance poised to transform diagnostic radiology, researchers have harnessed the power of convolutional neural networks (CNNs) to automate the scoring of computed tomography (CT) scans of the paranasal sinuses. This innovative approach promises to standardize and expedite the evaluation of chronic rhinosinusitis (CRS), a condition that affects millions worldwide and has long [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">242360</post-id>	</item>
	</channel>
</rss>
