Lightweight Models Beat LLMs for Hospital Discharge Prediction

Researchers found that traditional machine learning models outperform fine-tuned large language models at predicting next-day discharge in spine surgery units using clinical notes. TF-IDF with LGBM achieved the best performance, suggesting resource-efficient, interpretable models may be more practical for imbalanced clinical prediction tasks than compact LLMs.