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	<title>data-driven healthcare** &#8211; BIOENGINEER.ORG</title>
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		<title>Enhancing Parkinson’s Progression Scales with Computation</title>
		<link>https://bioengineer.org/enhancing-parkinsons-progression-scales-with-computation/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 23 Jan 2026 14:28:43 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[clinical neurology innovation** **Kısa açıklama:** 1. **Parkinson progression scales optimization:** Makalenin temel odağı]]></category>
		<category><![CDATA[data-driven healthcare**]]></category>
		<category><![CDATA[geleneksel ölçeklerin (UPDRS gibi) hesaplamalı yöntemler]]></category>
		<category><![CDATA[Hastalık ilerleme optimizasyonu]]></category>
		<category><![CDATA[Hesaplamalı nöroloji]]></category>
		<category><![CDATA[İşte içeriğe uygun 5 etiket: **Parkinson progression scales optimization]]></category>
		<category><![CDATA[İşte içeriğe uygun 5 Türkçe etiket: **Parkinson hastalığı ölçekleri]]></category>
		<category><![CDATA[Kişiselleştirilmiş nörolojik bakım** **Açıklama:** 1. **Parkinson hastalığı]]></category>
		<category><![CDATA[Machine learning in neurology]]></category>
		<category><![CDATA[Makine öğrenimi ile tıp]]></category>
		<category><![CDATA[personalized medicine in Parkinson’s]]></category>
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					<description><![CDATA[In a groundbreaking advance set to transform the landscape of Parkinson’s disease management, a team of researchers has introduced novel computational methods to optimize disease progression scales, promising unprecedented precision and potential for personalized therapeutic approaches. Parkinson’s disease (PD), a progressive neurodegenerative disorder characterized primarily by motor dysfunction and a spectrum of non-motor symptoms, has [&#8230;]]]></description>
		
		
		
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		<title>Evaluating Physicians’ Use of Blood Management Decision Support</title>
		<link>https://bioengineer.org/evaluating-physicians-use-of-blood-management-decision-support/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Fri, 21 Nov 2025 16:19:57 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[blood management]]></category>
		<category><![CDATA[clinical decision support systems]]></category>
		<category><![CDATA[data-driven healthcare**]]></category>
		<category><![CDATA[physician experiences]]></category>
		<category><![CDATA[technology in healthcare]]></category>
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					<description><![CDATA[In a rapidly evolving healthcare landscape, the integration of technology into clinical practices is not just an option; it is becoming a necessity. The introduction of Clinical Decision Support Systems (CDSS) is one such technological advancement that has shown promise in improving patient outcomes, particularly within the domain of patient blood management. In a groundbreaking [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">299587</post-id>	</item>
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