Healthcare Innovation November 18, 2024
Mount Sinai researchers find that by grouping up to 50 clinical tasks together, LLMs can handle them simultaneously without a significant drop in accuracy
Researchers at the Icahn School of Medicine at Mount Sinai have identified strategies for using large language models (LLMs) in health systems while maintaining cost efficiency and performance.
The findings, published in the Nov. 18 online issue of npj Digital Medicine, provide insights into how health systems can leverage LLMs to automate tasks efficiently, saving time and reducing operational costs while ensuring these models remain reliable even under high task loads.
The researchers note that LLMs, such as OpenAI’s GPT-4, offer encouraging ways to automate and streamline workflows by assisting with various tasks. However, continuously running...
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