Toward digital twins in the intensive care unit: a medication management case study

Abstract:

Objective To evaluate the efficacy of digital twins developed using a large language model (LLaMA-3), fine-tuned with Low-Rank Adapters (LoRA) on intensive care units (ICU) physician notes, and to determine whether specialty-specific training enhances treatment recommendation accuracy compared to other ICU specialties or zero-shot baselines. Materials and Methods Digital twins were created using LLaMA-3 fine-tuned on discharge summaries from the Medical Information Mart for Intensive Care III dataset, where medications were masked to construct training and testing datasets. The medical ICU dataset (1000 notes) was used for evaluation, and performance was assessed using Bidirectional Encoder Representations from Transformers Score (BERTScore) and ROUGE-L. A zero-shot baseline model, relying solely on contextual instructions without training, was also …