mlsanityData to 7 Oct 2026

ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration

arXiv 2410.02551 ↗First posted 3 Oct 2024cs.LG cs.AI cs.CLcited by 23

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

We introduce ColaCare, a framework that enhances Electronic Health Record (EHR) modeling through multi-agent collaboration driven by Large Language Models (LLMs). Our approach seamlessly integrates domain-specific expert models with LLMs to bridge the gap between structured EHR data and text-based reasoning. Inspired by the Multidisciplinary Team (MDT) approach used in clinical settings, ColaCare employs two types of agents: DoctorAgents and a MetaAgent, which collaboratively analyze patient data. Expert models process and generate predictions from numerical EHR data, while LLM agents produce reasoning references and decision-making reports within the MDT-driven collaborative consultation framework. The MetaAgent orchestrates the discussion, facilitating consultations and evidence-based debates among DoctorAgents, simulating diverse expertise in clinical decision-making. We additionally incorporate the Merck Manual of Diagnosis and Therapy (MSD) medical guideline within a retrieval-augmented generation (RAG) module for medical evidence support, addressing the challenge of knowledge currency. Extensive experiments conducted on three EHR datasets demonstrate ColaCare's superior performance in clinical mortality outcome and readmission prediction tasks, underscoring its potential to revolutionize clinical decision support systems and advance personalized precision medicine. All code, case studies and a questionnaire are available at the project website: https://colacare.netlify.app.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 26 of its 70 references that are in the map. First posted on arXiv 3 Oct 2024.

Builds on

26 of 70 references.

Closest ancestors · 2

Same direction, newest first

  1. 2024Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents5 May
  2. 2024AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator15 Feb

Other references · 24

  1. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  2. 2017On Calibration of Modern Neural Networkscited by 4,860
  3. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,416
  4. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,888
  5. 2018CBAM: Convolutional Block Attention Modulecited by 2,463
  6. 2022Large Language Models Encode Clinical Knowledgecited by 1,807
  7. 2024DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Modelcited by 1,093
  8. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  9. 2016RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanismcited by 344
  10. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 311
  11. 2023ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMscited by 297
  12. 2023Adapted Large Language Models Can Outperform Medical Experts in Clinical Text Summarizationcited by 244
12 more
  1. 2021Multi-Time Attention Networks for Irregularly Sampled Time Seriescited by 234
  2. 2023MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrievalcited by 182
  3. 2016GRAM: Graph-based Attention Model for Healthcare Representation Learningcited by 152
  4. 2022M3Care: Learning with Missing Modalities in Multimodal Healthcare Datacited by 71
  5. 2023GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphscited by 57
  6. 2019ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Contextcited by 56
  7. 2024A Closer Look at AUROC and AUPRC under Class Imbalancecited by 56
  8. 2019AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibrationcited by 50
  9. 2022A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Carecited by 10
  10. 2024Me LLaMA: Foundation Large Language Models for Medical Applicationscited by 10
  11. 2023PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representationscited by 9
  12. 2024ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Taskscited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 11; 2026: 11.

23 papers.

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  1. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Userscited by 32
  2. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  3. 2025HealthFlow: A Self-Evolving AI Agent with Meta Planning for Autonomous Healthcare Researchcited by 10
  4. 2024Multi-Agent Collaboration in Incident Response with Large Language Modelscited by 4
  5. 2025Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectivescited by 4
  6. 2026ClinicalAgents: Multi-Agent Orchestration for Clinical Decision Making with Dual-Memorycited by 4
  7. 2025AutoBnB-RAG: Enhancing Multi-Agent Incident Response with Retrieval-Augmented Generationcited by 3
  8. 2025LLM-Driven Collaborative Model for Untangling Commits via Explicit and Implicit Dependency Reasoningcited by 2
  9. 2025ConfAgents: A Conformal-Guided Multi-Agent Framework for Cost-Efficient Medical Diagnosiscited by 2
  10. 2025Grounded by Experience: Generative Healthcare Prediction Augmented with Hierarchical Agentic Retrievalcited by 1
  11. 2026Agentic AI in Healthcare & Medicine: A Seven-Dimensional Taxonomy for Empirical Evaluation of LLM-based Agentscited by 1
  12. 2026MedCoG: Maximizing LLM Inference Density in Medical Reasoning via Meta-Cognitive Regulationcited by 1
11 more
  1. 2026The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomycited by 1
  2. 2025Lessons Learned from Evaluation of LLM based Multi-agents in Safer Therapy Recommendationcited by 0
  3. 2025Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Makingcited by 0
  4. 2025DiscoVerse: Multi-Agent Pharmaceutical Co-Scientist for Traceable Drug Discovery and Reverse Translationcited by 0
  5. 2026MedCoRAG: Interpretable Hepatology Diagnosis via Hybrid Evidence Retrieval and Multispecialty Consensuscited by 0
  6. 2026From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoningcited by 0
  7. 2026TSAssistant: A Human-in-the-Loop Agentic Framework for Automated Target Safety Assessmentcited by 0
  8. 2026Trajectory-Aware Clinical Risk Prediction via Severity-Grounded Knowledge Graphs and Retrieval-Augmented Generationcited by 0
  9. 2026Patients-like-me: A Variational LM--GNN Framework for Explainable Clinical Predictioncited by 0
  10. 2026Role-Specialized Mixture-of-Agents with Open-Weight LLMs for Clinical Predictioncited by 0
  11. 2026ViSTA: A Simple Bridge Extends Visual Alignment to Clinical Time-Series Understanding in Multimodal LLMscited by 0

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  1. 2026AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks
  2. 2026EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse
  3. 2025A Knowledge-driven Adaptive Collaboration of LLMs for Enhancing Medical Decision-making
  4. 2024EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records
  5. 2026Small Agent Group is the Future of Digital Health
  6. 2025MedAgentBoard: Benchmarking Multi-Agent Collaboration with Conventional Methods for Diverse Medical Tasks
  7. 2024LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction
  8. 2026ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning