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	<title>Large language models Archives - HIT Leaders and News</title>
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		<title>Q&#038;A with Dr. Jay Anders, CMO of Medicomp Systems: How LLMs and AI Are Reshaping Healthcare—And Where They Fall Short</title>
		<link>https://us.hitleaders.news/qa/48049/qa-with-dr-jay-anders-cmo-of-medicomp-systems-how-llms-and-ai-are-reshaping-healthcare-and-where-they-fall-short/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=qa-with-dr-jay-anders-cmo-of-medicomp-systems-how-llms-and-ai-are-reshaping-healthcare-and-where-they-fall-short</link>
		
		<dc:creator><![CDATA[Jason Free]]></dc:creator>
		<pubDate>Thu, 24 Apr 2025 10:17:26 +0000</pubDate>
				<category><![CDATA[Q&A]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Large language models]]></category>
		<category><![CDATA[LLMs]]></category>
		<category><![CDATA[Medicomp Systems]]></category>
		<guid isPermaLink="false">https://us.hitleaders.news/?p=48049</guid>

					<description><![CDATA[<p>In this exclusive Q&#038;A, HIT Leaders &#038; News speaks with Dr. Jay Anders, Chief Medical Officer at Medicomp Systems, to explore both the promise and the pitfalls of deploying AI and LLM technologies in real-world clinical settings. Dr. Anders discusses why these tools must be implemented with caution, how data quality remains a fundamental hurdle, and what providers can do to ensure AI supports—rather than undermines—quality care.</p>
<p>The post <a href="https://us.hitleaders.news/qa/48049/qa-with-dr-jay-anders-cmo-of-medicomp-systems-how-llms-and-ai-are-reshaping-healthcare-and-where-they-fall-short/">Q&#038;A with Dr. Jay Anders, CMO of Medicomp Systems: How LLMs and AI Are Reshaping Healthcare—And Where They Fall Short</a> appeared first on <a href="https://us.hitleaders.news">HIT Leaders and News</a>.</p>
]]></description>
		
		
		
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		<item>
		<title>Is AI in Medicine Playing Fair?</title>
		<link>https://us.hitleaders.news/academic-research/47859/is-ai-in-medicine-playing-fair/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=is-ai-in-medicine-playing-fair</link>
		
		<dc:creator><![CDATA[Jason Free]]></dc:creator>
		<pubDate>Tue, 15 Apr 2025 13:24:22 +0000</pubDate>
				<category><![CDATA[Academic Research]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Icahn School of Medicine]]></category>
		<category><![CDATA[Large language models]]></category>
		<category><![CDATA[LLMs]]></category>
		<category><![CDATA[Mount Sinai]]></category>
		<guid isPermaLink="false">https://us.hitleaders.news/?p=47859</guid>

					<description><![CDATA[<p>“Our research provides a framework for AI assurance, helping developers and health care institutions design fair and reliable AI tools,” says co-senior author Eyal Klang, MD, Chief of Generative-AI in the Windreich Department of Artificial Intelligence and Human Health at the Icahn School of Medicine at Mount Sinai. “By identifying when AI shifts its recommendations based on background rather than medical need, we inform better model training, prompt design, and oversight. Our rigorous validation process tests AI outputs against clinical standards, incorporating expert feedback to refine performance. This proactive approach not only enhances trust in AI-driven care but also helps shape policies for better health care for all.” </p>
<p>The post <a href="https://us.hitleaders.news/academic-research/47859/is-ai-in-medicine-playing-fair/">Is AI in Medicine Playing Fair?</a> appeared first on <a href="https://us.hitleaders.news">HIT Leaders and News</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Layer Health Secures $21M to Scale AI Chart Review: What It Means for Clinical Data Integrity and Hospital Operations</title>
		<link>https://us.hitleaders.news/core-categories/revenue-cycle-management-and-finance/47815/layer-health-secures-21m-to-scale-ai-chart-review-what-it-means-for-clinical-data-integrity-and-hospital-operations/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=layer-health-secures-21m-to-scale-ai-chart-review-what-it-means-for-clinical-data-integrity-and-hospital-operations</link>
		
		<dc:creator><![CDATA[Jason Free]]></dc:creator>
		<pubDate>Thu, 10 Apr 2025 12:59:42 +0000</pubDate>
				<category><![CDATA[Revenue Cycle Management & Finance ]]></category>
		<category><![CDATA[Clinical Data]]></category>
		<category><![CDATA[Hospital Operations]]></category>
		<category><![CDATA[Large language models]]></category>
		<category><![CDATA[Layer Health]]></category>
		<category><![CDATA[LLMs]]></category>
		<guid isPermaLink="false">https://us.hitleaders.news/?p=47815</guid>

					<description><![CDATA[<p>Layer Health, a healthcare AI company founded by former MIT, Harvard, Microsoft, and Google technologists, has raised $21 million in Series A funding to expand its chart abstraction and clinical inference platform. The round was led by Define Ventures, with participation from Flare Capital, GV (formerly Google Ventures), and MultiCare Capital Partners—underscoring the platform’s relevance across health systems, digital health, and life sciences.</p>
<p>The post <a href="https://us.hitleaders.news/core-categories/revenue-cycle-management-and-finance/47815/layer-health-secures-21m-to-scale-ai-chart-review-what-it-means-for-clinical-data-integrity-and-hospital-operations/">Layer Health Secures $21M to Scale AI Chart Review: What It Means for Clinical Data Integrity and Hospital Operations</a> appeared first on <a href="https://us.hitleaders.news">HIT Leaders and News</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Despite AI Advancements, Human Oversight Remains Essential</title>
		<link>https://us.hitleaders.news/academic-research/42652/despite-ai-advancements-human-oversight-remains-essential/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=despite-ai-advancements-human-oversight-remains-essential</link>
		
		<dc:creator><![CDATA[Jason Free]]></dc:creator>
		<pubDate>Mon, 29 Apr 2024 13:21:23 +0000</pubDate>
				<category><![CDATA[Academic Research]]></category>
		<category><![CDATA[AI]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Icahn School of Medicine]]></category>
		<category><![CDATA[Large language models]]></category>
		<category><![CDATA[Mount Sinai]]></category>
		<category><![CDATA[Mount Sinai Health System]]></category>
		<guid isPermaLink="false">https://us.hitleaders.news/?p=42652</guid>

					<description><![CDATA[<p>State-of-the-art artificial intelligence systems known as large language models (LLMs) are poor medical coders, according to researchers at the Icahn School of Medicine at Mount Sinai.</p>
<p>The post <a href="https://us.hitleaders.news/academic-research/42652/despite-ai-advancements-human-oversight-remains-essential/">Despite AI Advancements, Human Oversight Remains Essential</a> appeared first on <a href="https://us.hitleaders.news">HIT Leaders and News</a>.</p>
]]></description>
		
		
		
			</item>
		<item>
		<title>Study Assesses GPT-4&#8217;s Potential to Perpetuate Racial, Gender Biases in Clinical Decision Making</title>
		<link>https://us.hitleaders.news/academic-research/41845/study-assesses-gpt-4s-potential-to-perpetuate-racial-gender-biases-in-clinical-decision-making/?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=study-assesses-gpt-4s-potential-to-perpetuate-racial-gender-biases-in-clinical-decision-making</link>
		
		<dc:creator><![CDATA[Jason Free]]></dc:creator>
		<pubDate>Wed, 27 Dec 2023 15:50:01 +0000</pubDate>
				<category><![CDATA[Academic Research]]></category>
		<category><![CDATA[Brigham and Women’s Hospital]]></category>
		<category><![CDATA[Clinical Decision Making]]></category>
		<category><![CDATA[Large language models]]></category>
		<guid isPermaLink="false">https://us.hitleaders.news/?p=41845</guid>

					<description><![CDATA[<p>Large language models (LLMs) like ChatGPT and GPT-4 have the potential to assist in clinical practice to automate administrative tasks, draft clinical notes, communicate with patients, and even support clinical decision making.</p>
<p>The post <a href="https://us.hitleaders.news/academic-research/41845/study-assesses-gpt-4s-potential-to-perpetuate-racial-gender-biases-in-clinical-decision-making/">Study Assesses GPT-4&#8217;s Potential to Perpetuate Racial, Gender Biases in Clinical Decision Making</a> appeared first on <a href="https://us.hitleaders.news">HIT Leaders and News</a>.</p>
]]></description>
		
		
		
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