LLMs translate clinical trial protocols into formal logic for "Symbolic Biomedicine"

Researchers have developed a new workflow called CT-TEL that uses Large Language Models (LLMs) to convert unstructured clinical trial protocols into a formal logic representation known as Temporal Ensemble Logic (TEL). This approach aims to overcome the limitations of free-text documentation, which hinders automated reasoning and simulation in clinical trials. The CT-TEL workflow was applied to 23 real-world trials, and a back-translation evaluation indicated that LLMs can effectively map informal protocols to computable logic, supporting the emerging field of "Symbolic Biomedicine." AI

IMPACT Enables more robust automated reasoning and simulation for clinical trials by formalizing unstructured data.

RANK_REASON The cluster contains an academic paper detailing a new methodology and its application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• arXiv
• CT-TEL
• Hugging Face
• Large Language Models
• Symbolic Biomedicine
• Temporal Ensemble Logic

• paper
• product

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