mlsanityData to 7 Oct 2026

EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysis

arXiv 2510.25628 ↗First posted 29 Oct 2025cs.CLcited by 17

On the map: LLM reasoning → Clinical and biomedical applications

Abstract (arXiv)

Electronic Health Records (EHRs) contain rich yet complex information, and their automated analysis is critical for clinical decision-making. Despite recent advances of large language models (LLMs) in clinical workflows, their ability to analyze EHRs remains limited due to narrow task coverage and lack of EHR-oriented reasoning capabilities. This paper aims to bridge the gap, specifically, we present EHR-Ins, a large-scale, comprehensive EHR reasoning instruction dataset, comprising 300k high-quality reasoning cases and 4M non-reasoning cases across 42 distinct EHR tasks. Its core innovation is a thinking-graph-driven framework that enables to generate high-quality reasoning data at scale. Based on it, we develop EHR-R1, a series of reasoning-enhanced LLMs with up to 72B parameters tailored for EHR analysis. Through a multi-stage training paradigm, including domain adaptation, reasoning enhancement, and reinforcement learning, EHR-R1 systematically acquires domain knowledge and diverse reasoning capabilities, enabling accurate and robust EHR analysis. Lastly, we introduce EHR-Bench, a new benchmark curated from MIMIC-IV, spanning 42 tasks, to comprehensively assess reasoning and prediction across EHR scenarios. In experiments, we show that the resulting EHR-R1 consistently outperforms state-of-the-art commercial and open-source LLMs (including DeepSeek-V3 and GPT-4o), surpassing GPT-4o by over 30 points on MIMIC-Bench and achieving a 10% higher zero-shot AUROC on EHRSHOT. Collectively, EHR-Ins, EHR-R1, and EHR-Bench have significantly advanced the development for more reliable and clinically relevant EHR analysis.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 34 of its 45 references that are in the map. First posted on arXiv 29 Oct 2025.

Builds on

34 of 45 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learning30 May
  2. 2025MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs1 Apr
  3. 2025Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases6 Mar

Other references · 31

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2024The Llama 3 Herd of Modelscited by 14,192
  4. 2025Qwen3 Technical Reportcited by 8,195
  5. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
  6. 2024GPT-4o System Cardcited by 4,467
  7. 2024Qwen2 Technical Reportcited by 2,076
  8. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  9. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  10. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 630
  11. 2025MedGemma Technical Reportcited by 398
  12. 2021TAPEX: Table Pre-training via Learning a Neural SQL Executorcited by 233
19 more
  1. 2019MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-IIIcited by 121
  2. 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Modelscited by 101
  3. 2024Zero Shot Health Trajectory Prediction Using Transformercited by 74
  4. 2025MedHELM: Holistic Evaluation of Large Language Models for Medical Taskscited by 60
  5. 2025Baichuan-M1: Pushing the Medical Capability of Large Language Modelscited by 41
  6. 2022An Extensive Data Processing Pipeline for MIMIC-IVcited by 39
  7. 2021HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Datacited by 38
  8. 2024Towards Evaluating and Building Versatile Large Language Models for Medicinecited by 38
  9. 2024Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulatorcited by 36
  10. 2019Benchmarking machine learning models on multi-centre eICU critical care datasetcited by 35
  11. 2025Large Language Models are Powerful Electronic Health Record Encoderscited by 25
  12. 2024Biomedical Large Languages Models Seem not to be Superior to Generalist Models on Unseen Medical Datacited by 21
  13. 2024ReflecTool: Towards Reflection-Aware Tool-Augmented Clinical Agentscited by 20
  14. 2025Foundation Model of Electronic Medical Records for Adaptive Risk Estimationcited by 17
  15. 2025HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Researchcited by 10
  16. 2025A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Modelscited by 8
  17. 2024Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failurecited by 3
  18. 2024PrecLLM: A Privacy-Preserving Framework for Efficient Clinical Annotation Extraction from Unstructured EHRs using Small-Scale LLMscited by 3
  19. 2023Detection and prediction of clopidogrel treatment failures using longitudinal structured electronic health recordscited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 17.

17 papers.

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  1. 2026EHR-RAG: Bridging Long-Horizon Structured Electronic Health Records and Large Language Models via Enhanced Retrieval-Augmented Generationcited by 6
  2. 2026Medical Reasoning with Large Language Models: A Survey and MR-Benchcited by 4
  3. 2026ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical Reasoningcited by 3
  4. 2026LLMs can construct powerful representations and streamline sample-efficient supervised learningcited by 2
  5. 2026CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubricscited by 2
  6. 2026Clin-JEPA: A Multi-Phase Co-Training Framework for Joint-Embedding Predictive Pretraining on EHR Patient Trajectoriescited by 2
  7. 2026EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMscited by 2
  8. 2026Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modelingcited by 1
  9. 2026A Causal Language Modeling Detour Improves Encoder Continued Pretrainingcited by 1
  10. 2026Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoningcited by 1
  11. 2026C-MIG: Multi-view Information Gain-based Retrieval-Augmented Generation for Clinical Diagnosis Reasoningcited by 0
  12. 2026ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoningcited by 0
5 more
  1. 2026TRIAGE: Dialectical Reasoning for Explainable Risk Prediction on Irregularly Sampled Medical Time Series with LLMscited by 0
  2. 2026LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learningcited by 0
  3. 2026MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveformscited by 0
  4. 2026ReLMem: Learning Recurrent Memory for Longitudinal EHR Modelingcited by 0
  5. 2026GLoC-EHR: Evidence-Cited Clinical Reasoning over Global Context and Local EHR Eventscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Toward Better EHR Reasoning in LLMs: Reinforcement Learning with Expert Attention Guidance
  2. 2026GraphWalker: Patient Analogy Meets Information Gain for Clinical Reasoning with Large Language Models
  3. 2025EHRStruct: A Comprehensive Benchmark Framework for Evaluating Large Language Models on Structured Electronic Health Record Tasks
  4. 2026EHR-Complex: Benchmarking Medical Agents for Complex Clinical Reasoning
  5. 2026Reinforcement Learning over Patient Trajectories for Clinical Reasoning in EHR Foundation Models
  6. 2026Beyond Prediction: Longitudinal Reasoning in EHR-Integrated Clinical AI ↗
  7. 2025A Specialized Large Language Model for Clinical Reasoning and Diagnosis in Rare Diseases
  8. 2025Extracting OPQRST in Electronic Health Records using Large Language Models with Reasoning