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Bridging Gaps in Cancer Care: Utilizing Large Language Models for Accessible Dietary Recommendations.

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  • 1Department of Radiation Oncology, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA 19107, USA.

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Large language models (LLMs) can offer personalized cancer nutrition advice, adapting to patient needs like culture and budget. This technology can improve health equity for those lacking access to specialized care.

Keywords:
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Area of Science:

  • Oncology
  • Nutritional Science
  • Artificial Intelligence

Background:

  • Weight management significantly impacts cancer recurrence and survival.
  • Nutritional oncology counseling faces insurance coverage gaps, creating disparities in patient care.
  • Personalized nutrition advice is crucial for cancer patients, necessitating innovative delivery methods.

Purpose of the Study:

  • To evaluate the capability of large language models (LLMs) in providing personalized dietary advice for breast cancer patients.
  • To compare LLM-generated dietary plans with those created by oncology dietitians.

Main Methods:

  • Thirty-one prompt templates assessed ChatGPT and Gemini responses across eight variables (stage, comorbidity, location, culture, age, guideline, budget, store).
  • Seven prompts were answered by four board-certified oncology dietitians for comparison.
  • Nutritional content, qualitative aspects, calorie, and macronutrient adherence were quantitatively analyzed.

Main Results:

  • LLMs adapted meal plans to location, culture, and budget, but not age, disease stage, or comorbidities.
  • Gemini offered more detailed responses, including visuals and pricing.
  • LLM-generated plans showed better macronutrient ratio adherence to Acceptable Macronutrient Distribution Ranges than dietitian plans.
  • Calorie content adherence to USDA estimates was higher in dietitian-generated diets.

Conclusions:

  • LLMs can deliver personalized dietary advice, enhancing health equity for cancer patients with limited access to care.
  • LLM-generated grocery lists and meal plans accommodate diverse food access, socioeconomic status, and cultural preferences.
  • While differences exist, LLM and dietitian meal plans showed no significant overall variation, indicating LLM applicability.