However, some medical experts have cautioned against relying too heavily on Open Medical-LLM, warning that it could lead to ill-informed deployments. They argue that the gap between the test environment and actual clinical practice is significant. Hugging Face research scientist Clémentine Fourrier agreed, stating that these leaderboards should only be used as a first approximation and that a deeper phase of testing is always needed. The article also highlights that none of the 139 AI-related medical devices approved by the U.S. FDA to date use generative AI, indicating the challenges of translating lab performance to real-world applications.
Key takeaways:
- Hugging Face, in partnership with Open Life Science AI and the University of Edinburgh’s Natural Language Processing Group, has released a benchmark test called Open Medical-LLM to evaluate the performance of generative AI models in healthcare.
- Open Medical-LLM combines existing test sets to assess models' knowledge in medical and related fields, using multiple choice and open-ended questions from U.S. and Indian medical licensing exams and college biology test question banks.
- Despite the potential of the benchmark, some medical experts warn against relying too heavily on it, highlighting the gap between test environments and actual clinical practice.
- Real-world testing of AI tools in healthcare has proven challenging, with none of the 139 AI-related medical devices approved by the U.S. FDA to date using generative AI.