activity
20232026
most citedLeveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study

91 citations · 111 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Measuring Mechanistic Uncertainty in Large Language Models via Causal Robustness

Aneesh Komanduri, Majid Afshar, Timothy A. Miller +1

Large language models (LLMs) are increasingly used in critical domains, where their susceptibility to hallucinations makes reliable and interpretable uncertainty quantification ess…

cs.AI2024

Position Paper On Diagnostic Uncertainty Estimation from Large Language Models: Next-Word Probability Is Not Pre-test Probability

Yanjun Gao, Skatje Myers, Shan Chen +7

Large language models (LLMs) are being explored for diagnostic decision support, yet their ability to estimate pre-test probabilities, vital for clinical decision-making, remains l…

cs.CL2024★ 17 cited

Lessons Learned on Information Retrieval in Electronic Health Records: A Comparison of Embedding Models and Pooling Strategies

Skatje Myers, Timothy A. Miller, Yanjun Gao +4

Objective: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation…

cs.CL2024

When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?

Yanjun Gao, Skatje Myers, Shan Chen +5

The introduction of Large Language Models (LLMs) has advanced data representation and analysis, bringing significant progress in their use for medical questions and answering. Desp…

cs.CL2024

Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data

Shan Chen, Jack Gallifant, Marco Guevara +5

Generative models have been showing potential for producing data in mass. This study explores the enhancement of clinical natural language processing performance by utilizing synth…

cs.CL2023★ 3 cited

The impact of responding to patient messages with large language model assistance

Shan Chen, Marco Guevara, Shalini Moningi +12

Documentation burden is a major contributor to clinician burnout, which is rising nationally and is an urgent threat to our ability to care for patients. Artificial intelligence (A…

cs.CL2023★ 91 cited

Leveraging Medical Knowledge Graphs Into Large Language Models for Diagnosis Prediction: Design and Application Study

Yanjun Gao, Ruizhe Li, Emma Croxford +6

Electronic Health Records (EHRs) and routine documentation practices play a vital role in patients' daily care, providing a holistic record of health, diagnoses, and treatment. How…