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		<title>Physicists&#8217; Reaction-Diffusion Equations Inspire Sharper AI for Skin Cancer Diagnosis</title>
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		<pubDate>Tue, 06 Oct 2026 00:56:31 +0000</pubDate>
				<category><![CDATA[Technology]]></category>
		<category><![CDATA[Attention Mechanism]]></category>
		<category><![CDATA[computer-aided diagnosis]]></category>
		<category><![CDATA[convolutional neural networks]]></category>
		<category><![CDATA[deep learning]]></category>
		<category><![CDATA[dermoscopy]]></category>
		<category><![CDATA[Explainable AI]]></category>
		<category><![CDATA[Medical Imaging]]></category>
		<category><![CDATA[melanoma]]></category>
		<category><![CDATA[reaction-diffusion]]></category>
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		<category><![CDATA[SHAP]]></category>
		<category><![CDATA[skin cancer]]></category>
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					<description><![CDATA[A new deep learning model that embeds Turing-inspired reaction-diffusion mathematics and attention mechanisms into a ResNet50 backbone classifies dermoscopic images of melanoma and benign nevi with 94.35 percent accuracy while offering explainable visual justifications for its decisions.]]></description>
		
		
		
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