Large language models (LLMs) are used to seek health information. Guidelines for evidence-based health communication require the presentation of the best available evidence to support informed decision-making. We investigate the prompt-dependent guideline compliance of…
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Large language models (LLMs) are transforming the landscape of healthcare research, yet their role in qualitative analysis remains underexplored. This study compares human-led and LLM-assisted approaches to analyzing cancer patient narratives, using 33 semi-structured…
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Artificial intelligence (AI), particularly large language models (LLMs), is increasingly integrated into mental health care. This study examined racial bias in psychiatric diagnosis and treatment across four leading LLMs: Claude, ChatGPT, Gemini, and NewMes-15…
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Mass General Brigham researchers see value in a hybrid approach that makes use of generative artificial intelligence to diagnose patients. Comparing two arge language models – OpenAI’s GPT-4 and Google’s Gemini 1.5 – with its…
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Extracting structured data from free-text medical records at scale is laborious, and traditional approaches struggle in complex clinical domains. We present a novel, end-to-end pipeline leveraging large language models (LLMs) for highly accurate information…
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New York-based White Plains Hospital is collaborating with Layer Health, an AI-enabled chart review company, to automate reporting across multiple clinical registries and accelerate the chart review process.White Plains Hospital participates in numerous clinical…
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Large language models like ChatGPT are finding their way into healthcare, business, and everyday life. The study of mechanistic interpretability may help us create safer, more trustworthy algorithms by “looking under the hood.”
By Paul…
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Tech giant Microsoft announced it is adding Elon Musk’s AI startup xAI’s Grok 3 to its Azure platform. Grok 3 and Grok 3 mini will be available through Azure’s AI Foundry platform, which allows developers…
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Detailed social determinants of health (SDoH) is often buried within clinical text in EHRs. Most current NLP efforts for SDoH have limitations, investigating limited factors, deriving data from a single institution, using specific patient…
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Artificial Intelligence can mitigate the global shortage of medical diagnostic personnel but requires large-scale annotated datasets to train clinical algorithms. Natural Language Processing (NLP), including Large Language Models (LLMs), shows great potential for annotating…
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