Tag
An analysis by Blue Cross Blue Shield Association indicates that AI coding tools in hospitals have led to a $942 million increase in healthcare costs over two years, prompting discussions on AI's impact between insurers and tech developers.
The article introduces LearnActCoder, a role-aware error memory framework that adapts clinical coding agents by converting errors into structured lessons, improving CPT coding performance without model weight updates.
Proposes a deep neural model combining multi-layer temporal convolutional networks with label-wise attention for medical coding, achieving significant improvements in F1 and recall scores over previous state-of-the-art.
This empirical study investigates whether post-training (supervised fine-tuning and reinforcement learning) can improve LLMs' performance on automated ICD coding, introducing a diagnostic curriculum called PHI that extends GRPO to refine missed-code cases. Results show that prompting-only evaluation underestimates LLM potential, with SFT providing the main capability jump and RL further improving performance.