arXiv AI October 15, 2026 By Mahdi Alkaeed, Sofiat Abioye, Adnan Qayyum, Yosra Magdi Mekki, Ilhem Berrou, Mohamed Abdallah, Ala Al-Fuqaha, Muhammad Bilal, Junaid Qadir

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

Read the original on arXiv AI →

The paper surveys open, non‑proprietary large language models (LLMs) and AI foundation models (AIFMs) for clinical use, presenting a taxonomy of current state‑of‑the‑art models. It empirically tests open‑weight LLMs on a personalized‑prescription task, finding that they match or surpass a proprietary baseline in overall suitability accuracy, especially when combined with Retrieval‑Augmented Generation (RAG). A subjective evaluation by blinded raters shows mixed effects of RAG on perceived suitability across multiple dimensions, and the authors discuss ethical risks and the need for responsible deployment.

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