Papers by Jesus Felix B. Valenzuela
Are LLMs reliable? An exploration of the reliability of large language models in clinical note generation (2025.acl-industry)
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Kristine Ann M. Carandang, Jasper Meynard Arana, Ethan Robert Casin, Christopher Monterola, Daniel Stanley Tan, Jesus Felix B. Valenzuela, Christian Alis
| Challenge: | Clinical note generation (CNG) tools are being developed to address extended working hours and healthcare provider fatigue. |
| Approach: | They evaluate the reliability of 12 open-weight and proprietary LLMs from Anthropic, Meta, Mistral, and OpenAI in CNG in terms of their ability to generate notes that are string equivalent (consistency rate), have the same meaning (semantic consistency) and are correct (symbol similarity) |
| Outcome: | The results show that the LLMs generated notes that are string equivalent (consistency rate), have the same meaning (semantic consistency) and are correct (symbol similarity) overall, Meta’s Llama 70B was the most reliable, followed by Mistral’s Small model. |