Analyzing Provider Case Spectrum in Emergency Medicine with AI
We’re utilizing LLMs and big data to answer a critical question: What spectrum of cases has each Emergency Medicine provider managed? By analyzing comprehensive clinical data beyond discharge diagnoses, it offers a detailed view of provider experience. The findings will guide targeted educational efforts, with future work incorporating social determinants of health to deepen the analysis.
Will AI take my job?
Exploring the potential impact of artificial intelligence on medical practice, examining the extent to which AI technologies could augment or replace traditional physician tasks.
LLM Computer Use for Automated Chart Review
Utilize Large Language Models (LLMs) to automate medical chart review, transforming traditional manual review into an efficient, AI-powered process. By leveraging LLMs' natural language processing capabilities, we aim to reduce physician workload while maintaining high accuracy in medical record analysis
Modeling CT Utilization and Practice Patterns in Emergency Medicine
Focuses on developing predictive models to estimate CT scan utilization in the Emergency Department. By analyzing provider-specific case data, the model will assess how likely a patient is to receive a CT scan and whether it was appropriately ordered. The study also examines how individual providers’ resource utilization patterns influence their colleagues’ practices. Insights from this work will help standardize CT use and optimize resource allocation in clinical decision-making.