PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation
The study evaluated small-parameter LLMs running entirely on-device to safely resolve clinical acronyms in medical text without sending private patient data to external servers. A cascaded pipeline using a general model for detection and a domain-specific model for expansion significantly improved accuracy, showing that specialized local models can provide high-fidelity clinical support privately.