Clinical context, guidelines, and patient plans are used to prioritize concepts, expanding EHR queries with fewer false positives and negatives.
Real-time haptic feedback and 3D tool tracking improve depth perception and multi-tool coordination in endovascular procedure training.
Machine learning infers grouper and supporting clinical codes from incomplete EMRs, improving billing accuracy and direct-to-bill speed.
Machine learning infers supporting clinical codes from incomplete EMRs to improve DRG grouping accuracy, confidence scoring, and billing speed.
An LLM-driven course interface adapts avatar responses and pose demonstrations to user prompts, improving personalized interactive learning.