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	<title>Ethical AI in Healthcare &#8211; BIOENGINEER.ORG</title>
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		<title>Doctors’ Views on AI Chatbots in Clinical Decisions</title>
		<link>https://bioengineer.org/doctors-views-on-ai-chatbots-in-clinical-decisions/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Thu, 22 Jan 2026 21:33:46 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[Clinical Decision-Making]]></category>
		<category><![CDATA[clinical decision-making support]]></category>
		<category><![CDATA[Ethical AI in Healthcare]]></category>
		<category><![CDATA[Healthcare Technology` **Kısa açıklama:** * **AI Chatbots:** Makalenin temel konusunu doğrudan belirtiyor. * **Clinical Decision-Making:** AI'nın uygulandığı özel alanı vurguluyor. *]]></category>
		<category><![CDATA[İşte 5 uygun etiket: **AI in clinical settings]]></category>
		<category><![CDATA[İşte bu içerik için 5 uygun etiket: `AI Chatbots]]></category>
		<category><![CDATA[medical ethics]]></category>
		<category><![CDATA[Physician perspectives]]></category>
		<category><![CDATA[Physician perspectives on AI]]></category>
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					<description><![CDATA[The intersection of artificial intelligence and healthcare is a hotbed of innovation, exploration, and critical analysis. As the medical industry advances, a growing number of physicians are looking to AI-powered tools, particularly chatbots, to aid in clinical decision-making. A recent study titled “I Double Checked It with My Own Knowledge: Physician Perspectives on the Use [&#8230;]]]></description>
		
		
		
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		<title>Empowering Nursing Students in the AI Age</title>
		<link>https://bioengineer.org/empowering-nursing-students-in-the-ai-age/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Sat, 10 Jan 2026 17:52:40 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[AI in Nursing Education]]></category>
		<category><![CDATA[Empowering Nursing Students]]></category>
		<category><![CDATA[Ethical AI in Healthcare]]></category>
		<category><![CDATA[Healthcare Technology Integration]]></category>
		<category><![CDATA[Nursing Curriculum Development]]></category>
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					<description><![CDATA[In the rapidly evolving landscape of healthcare, the integration of artificial intelligence (AI) has emerged as a transformative force. Recent research conducted by Gouda et al. sheds light on the importance of equipping nursing students with the necessary knowledge and acceptance of AI technologies in a clinical setting. The study recognizes that nursing students, as [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">315742</post-id>	</item>
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		<title>Assessing ChatGPT’s Alignment with Geriatric Assessment Experts</title>
		<link>https://bioengineer.org/assessing-chatgpts-alignment-with-geriatric-assessment-experts/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Mon, 20 Oct 2025 21:10:02 +0000</pubDate>
				<category><![CDATA[Health]]></category>
		<category><![CDATA[AI alignment with healthcare experts]]></category>
		<category><![CDATA[ChatGPT in geriatric care]]></category>
		<category><![CDATA[Clinical reasoning in geriatrics]]></category>
		<category><![CDATA[Ethical AI in Healthcare]]></category>
		<category><![CDATA[Geriatric assessment AI evaluation]]></category>
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					<description><![CDATA[In recent years, conversational artificial intelligence has gained unprecedented traction, as machine learning technologies evolve rapidly, influencing various fields including healthcare. The emergence of advanced language models, particularly OpenAI’s ChatGPT, has sparked considerable interest among medical professionals and researchers. A recent study by Lilamand, Decaix, Gourraud, and their team explores the nuances of how different [&#8230;]]]></description>
		
		
		
		<post-id xmlns="com-wordpress:feed-additions:1">284032</post-id>	</item>
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		<title>Evaluating AI Accuracy in Pediatric Diagnosis Generation</title>
		<link>https://bioengineer.org/evaluating-ai-accuracy-in-pediatric-diagnosis-generation/</link>
		
		<dc:creator><![CDATA[Bioengineer]]></dc:creator>
		<pubDate>Wed, 06 Aug 2025 16:18:25 +0000</pubDate>
				<category><![CDATA[Cancer]]></category>
		<category><![CDATA[AI Accuracy Assessment]]></category>
		<category><![CDATA[Ethical AI in Healthcare]]></category>
		<category><![CDATA[Large Language Models in Medicine]]></category>
		<category><![CDATA[Medical Imaging Analysis]]></category>
		<category><![CDATA[Pediatric Diagnosis Generation]]></category>
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					<description><![CDATA[In recent years, the proliferation of artificial intelligence technologies, particularly large language models (LLMs), has prompted a reevaluation of their potential applications in various fields. One area that has drawn significant attention is artificial intelligence’s capacity to assist in medical diagnosis, especially in pediatrics. A recent study published in Pediatr Radiol by Jung, Phillipi, Tran, [&#8230;]]]></description>
		
		
		
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