91 citations · 150 across the 10 of their papers we have counts for
11 papers
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…
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…
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…
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…
Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning
Brihat Sharma, Yanjun Gao, Timothy Miller +3
Generative artificial intelligence (AI) is a promising direction for augmenting clinical diagnostic decision support and reducing diagnostic errors, a leading contributor to medica…
Overview of the Problem List Summarization (ProbSum) 2023 Shared Task on Summarizing Patients' Active Diagnoses and Problems from Electronic Health Record Progress Notes
Yanjun Gao, Dmitriy Dligach, Timothy Miller +2
The BioNLP Workshop 2023 initiated the launch of a shared task on Problem List Summarization (ProbSum) in January 2023. The aim of this shared task is to attract future research ef…
Progress Note Understanding -- Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task
Yanjun Gao, Dmitriy Dligach, Timothy Miller +3
Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designe…
Summarizing Patients Problems from Hospital Progress Notes Using Pre-trained Sequence-to-Sequence Models
Yanjun Gao, Dmitriy Dligach, Timothy Miller +3
Automatically summarizing patients' main problems from daily progress notes using natural language processing methods helps to battle against information and cognitive overload in…
DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing
Yanjun Gao, Dmitriy Dligach, Timothy Miller +4
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priori…
Hierarchical Annotation for Building A Suite of Clinical Natural Language Processing Tasks: Progress Note Understanding
Yanjun Gao, Dmitriy Dligach, Timothy Miller +4
Applying methods in natural language processing on electronic health records (EHR) data is a growing field. Existing corpus and annotation focus on modeling textual features and re…
A Scoping Review of Publicly Available Language Tasks in Clinical Natural Language Processing
Yanjun Gao, Dmitriy Dligach, Leslie Christensen +7
Objective: to provide a scoping review of papers on clinical natural language processing (NLP) tasks that use publicly available electronic health record data from a cohort of pati…