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	<title>hematologic toxicity prediction &#8211; BIOENGINEER.ORG</title>
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		<title>Interpretable AI Predicts Toxicity in Cervical Cancer</title>
		<link>https://bioengineer.org/interpretable-ai-predicts-toxicity-in-cervical-cancer/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 06 Oct 2025 17:40:34 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[cervical cancer treatment]]></category>
		<category><![CDATA[clinical decision support systems]]></category>
		<category><![CDATA[hematologic toxicity prediction]]></category>
		<category><![CDATA[interpretable AI]]></category>
		<category><![CDATA[radiomics-dosimetrics integration]]></category>
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					<description><![CDATA[In a groundbreaking development poised to reshape oncological care, researchers have unveiled a sophisticated machine learning model capable of predicting hematologic toxicity (HT) in patients with advanced cervical cancer undergoing chemoradiotherapy. By harnessing the power of interpretable artificial intelligence and integrating multifaceted radiomic and dosimetric data, this novel approach promises to enhance clinical decision-making and [&#8230;]]]></description>
		
		
		
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