Benchmark evaluation of DeepSeek large language models in clinical decision-making.

ABSTRACT: Large language models (LLMs) are increasingly transforming medical applications. However, proprietary models such as GPT-4o face significant barriers to clinical adoption because they cannot be deployed on site within healthcare institutions, making them noncompliant with stringent privacy regulations. Recent advancements in open-source LLMs such as DeepSeek models offer a promising alternative because they allow efficient fine-tuning on local data in hospitals with advanced information technology infrastructure. Here, to demonstrate the clinical utility of DeepSeek-V3 and DeepSeek-R1, we benchmarked their performance on clinical decision support tasks against proprietary LLMs, including GPT-4o and Gemini-2.0 Flash Thinking Experimental. Using 125 patient cases with sufficient statistical

SUBMITTER: Sandmann S 

PROVIDER: S-EPMC12353792 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature