718 citations
- Harvard UniversityUS102 papers
- Massachusetts Institute of TechnologyUS20 papers
- Massachusetts General HospitalUS17 papers
- University College LondonGB10 papers
- Brigham and Women's HospitalUS9 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS8 papers
- Boston Children's MuseumUS8 papers
- Northeastern UniversityUS7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Loyola University ChicagoUS6 papers
- University of LausanneCH6 papers
- University of PennsylvaniaUS6 papers
12 papers · 1 filter
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
Skatje Myers, Dmitriy Dligach, Timothy A. Miller +6
Objective: To evaluate whether retrieval-augmented generation (RAG) can serve as an efficient alternative to long-context prompting for clinical reasoning over electronic health re…
Using tournaments to calculate AUROC for zero-shot classification with LLMs
WonJin Yoon, Ian Bulovic, Timothy A. Miller
Large language models perform surprisingly well on many zero-shot classification tasks, but are difficult to fairly compare to supervised classifiers due to the lack of a modifiabl…
Aspect-Oriented Summarization for Psychiatric Short-Term Readmission Prediction
WonJin Yoon, Boyu Ren, Spencer Thomas +4
Recent progress in large language models (LLMs) has enabled the automated processing of lengthy documents even without supervised training on a task-specific dataset. Yet, their ze…
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…
From Explainable to Interpretable Deep Learning for Natural Language Processing in Healthcare: How Far from Reality?
Guangming Huang, Yingya Li, Shoaib Jameel +2
Deep learning (DL) has substantially enhanced natural language processing (NLP) in healthcare research. However, the increasing complexity of DL-based NLP necessitates transparent…
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…