56 citations · 56 across the 2 of their papers we have counts for
5 papers
Evaluation of Causal Reasoning for Large Language Models in Contextualized Clinical Scenarios of Laboratory Test Interpretation
Balu Bhasuran, Mattia Prosperi, Karim Hanna +3
This study evaluates causal reasoning in large language models (LLMs) using 99 clinically grounded laboratory test scenarios aligned with Pearl's Ladder of Causation: association,…
HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate Class
James V. Roggeveen, Erik Y. Wang, Will Flintoft +42
Large language models (LLMs) have shown remarkable progress in mathematical problem-solving, but evaluation has largely focused on problems that have exact analytical solutions or…
Evaluating the Impact of Lab Test Results on Large Language Models Generated Differential Diagnoses from Clinical Case Vignettes
Balu Bhasuran, Qiao Jin, Yuzhang Xie +6
Differential diagnosis is crucial for medicine as it helps healthcare providers systematically distinguish between conditions that share similar symptoms. This study assesses the i…
AgentMD: Empowering Language Agents for Risk Prediction with Large-Scale Clinical Tool Learning
Qiao Jin, Zhizheng Wang, Yifan Yang +8
Clinical calculators play a vital role in healthcare by offering accurate evidence-based predictions for various purposes such as prognosis. Nevertheless, their widespread utilizat…
Quality of Answers of Generative Large Language Models vs Peer Patients for Interpreting Lab Test Results for Lay Patients: Evaluation Study
Zhe He, Balu Bhasuran, Qiao Jin +6
Lab results are often confusing and hard to understand. Large language models (LLMs) such as ChatGPT have opened a promising avenue for patients to get their questions answered. We…