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Trajectory-Aware Clinical Risk Prediction via Severity-Grounded Knowledge Graphs and Retrieval-Augmented Generation

arXiv 2607.18270 ↗First posted 2 Jun 2026cs.AI cs.CLcited by 0

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Abstract (arXiv)

While Electronic Health Records (EHRs) offer a wealth of clinical data, effectively augmenting a patient's records with heterogeneous external knowledge to predict the patient's clinical risk remains a significant challenge. Existing methods fail to capture disease severity, treatment responses, and nuanced clinical progression, due to data sparsity and the underutilization of unstructured clinical notes. To address these challenges, we propose TRACER (a trajectory-aware and clinically grounded prediction framework) that (1) constructs a medical knowledge graph enriched with severity information from medical literature, (2) retrieves clinically relevant, severity-weighted paths of a patient's progression from the knowledge graph, (3) extracts clinically relevant events from unstructured clinical notes, and (4) augments patient context with similar peer cases. Experiments on the MIMIC-III and MIMIC-IV datasets demonstrate large gains over state-of-the-art baselines, with up to 28.5% increase in Macro F1 score for the mortality prediction task, and 19.7% increase for the readmission prediction task.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 29 of its 58 references that are in the map. First posted on arXiv 2 Jun 2026.

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References · 29

  1. 2017Attention Is All You Needcited by 59,932
  2. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  3. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
  4. 2018An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modelingcited by 1,447
  5. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  6. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,271
  7. 2019ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmissioncited by 487
  8. 2016RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanismcited by 344
  9. 2024Benchmarking Retrieval-Augmented Generation for Medicinecited by 326
  10. 2023RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentationcited by 253
  11. 2016GRAM: Graph-based Attention Model for Healthcare Representation Learningcited by 152
  12. 2024Searching for Best Practices in Retrieval-Augmented Generationcited by 83
17 more
  1. 2023GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphscited by 57
  2. 2019ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Contextcited by 56
  3. 2019AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibrationcited by 50
  4. 2022A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Predictioncited by 48
  5. 2020StageNet: Stage-Aware Neural Networks for Health Risk Predictioncited by 47
  6. 2024Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrievalcited by 45
  7. 2023CPLLM: Clinical Prediction with Large Language Modelscited by 34
  8. 2024BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidencecited by 28
  9. 2024ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaborationcited by 23
  10. 2019TAPER: Time-Aware Patient EHR Representationcited by 22
  11. 2024RAM-EHR: Retrieval Augmentation Meets Clinical Predictions on Electronic Health Recordscited by 21
  12. 2021Context-aware Health Event Prediction via Transition Functions on Dynamic Disease Graphscited by 20
  13. 2024EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generationcited by 16
  14. 2024Large Language Model Capabilities in Perioperative Risk Prediction and Prognosticationcited by 11
  15. 2023PRISM: Mitigating EHR Data Sparsity via Learning from Missing Feature Calibrated Prototype Patient Representationscited by 9
  16. 2018Neural networks versus Logistic regression for 30 days all-cause readmission predictioncited by 8
  17. 2023Bio+Clinical BERT, BERT Base, and CNN Performance Comparison for Predicting Drug-Review Satisfactioncited by 3

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