mlsanityData to 7 Oct 2026

Dynamic Q&A of Clinical Documents with Large Language Models

arXiv 2401.10733 ↗First posted 19 Jan 2024cs.IR cs.AIcited by 4

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Abstract (arXiv)

Electronic health records (EHRs) house crucial patient data in clinical notes. As these notes grow in volume and complexity, manual extraction becomes challenging. This work introduces a natural language interface using large language models (LLMs) for dynamic question-answering on clinical notes. Our chatbot, powered by Langchain and transformer-based LLMs, allows users to query in natural language, receiving relevant answers from clinical notes. Experiments, utilizing various embedding models and advanced LLMs, show Wizard Vicuna's superior accuracy, albeit with high compute demands. Model optimization, including weight quantization, improves latency by approximately 48 times. Promising results indicate potential, yet challenges such as model hallucinations and limited diverse medical case evaluations remain. Addressing these gaps is crucial for unlocking the value in clinical notes and advancing AI-driven clinical decision-making.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 15 of its 48 references that are in the map. First posted on arXiv 19 Jan 2024.

Builds on

15 of 48 references.

References · 15

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3 more
  1. 2024RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculturecited by 80
  2. 2023ZeroQuant-V2: Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensationcited by 78
  3. 2020CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answeringcited by 26

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 2.

4 papers.

  1. 2024Evaluating Search Engines and Large Language Models for Answering Health Questionscited by 5
  2. 2024The Future of Intelligent Healthcare: A Systematic Analysis and Discussion on the Integration and Impact of Robots Using Large Language Models for Healthcarecited by 2
  3. 2026EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Recordscited by 1
  4. 2026HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answeringcited by 1