Retrieval-augmented generation for generative artificial intelligence in health care
Abstract Generative artificial intelligence has brought disruptive innovations in health care but faces certain challenges. Retrieval-augmented generation (RAG) enables models to generate more reliable content by leveraging the retrieval of external knowledge. In this perspective, we analyze the possible contributions that RAG could bring to health care in equity, reliability, and personalization. Additionally, we discuss the current limitations and challenges of implementing RAG in medical scen
Record details
Published: 25 January 2025
Source: OpenAlex
Category: Research
Topics: Bias & fairness · Healthcare
Retrieved: 14 July 2026
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How to cite this record
ethics.ai (25 January 2025), “Retrieval-augmented generation for generative artificial intelligence in health care,” evidence record 9772, https://ethics.ai/record/9772 (originally published by OpenAlex).
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