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      <title>Empowering Cancer Care with AI: A Jefferson Medical Student–Led Innovation</title>
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      <description>&lt;p&gt;I’m excited to share a new collaborative study I had the privilege of co-authoring, which was recently published in &lt;em&gt;Nutrients&lt;/em&gt;. Led by Jefferson medical student &lt;strong&gt;Julia Logan&lt;/strong&gt;, this work explores how large language models (LLMs) like ChatGPT and Gemini can deliver accessible, culturally sensitive dietary advice to cancer patients—many of whom lack access to professional nutritional counseling due to insurance limitations or socioeconomic barriers.&lt;/p&gt;
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&lt;p&gt;&lt;img alt=&#34;A schematic of LLM prompts designed to evaluate the dietary recommendations generated by ChatGPT and Gemini. A total of 31 zero-shot prompt templates with prompt variations within 8 categorical variables, including cancer stage, comorbidity, location, culture, age, dietary guideline, budget, and store, are shown. One variable was changed in each prompt. Seven of these prompts were selected (highlighted in gray) and four dietitians also responded to them.&#34; loading=&#34;lazy&#34; src=&#34;https://www.qradiomics.com/posts/2025-04-08-empowering-cancer-care-with-ai-a-jefferson-medical-student-led-innovation/images/image-1.png&#34;&gt;&lt;/p&gt;</description>
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