mlsanityData to 7 Oct 2026

Structured Semantics from Unstructured Notes: Language Model Approaches to EHR-Based Decision Support

arXiv 2506.06340 ↗First posted 1 Jun 2025cs.IR cs.AIcited by 7

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Abstract (arXiv)

The advent of large language models (LLMs) has opened new avenues for analyzing complex, unstructured data, particularly within the medical domain. Electronic Health Records (EHRs) contain a wealth of information in various formats, including free text clinical notes, structured lab results, and diagnostic codes. This paper explores the application of advanced language models to leverage these diverse data sources for improved clinical decision support. We will discuss how text-based features, often overlooked in traditional high dimensional EHR analysis, can provide semantically rich representations and aid in harmonizing data across different institutions. Furthermore, we delve into the challenges and opportunities of incorporating medical codes and ensuring the generalizability and fairness of AI models in healthcare.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 1 Jun 2025.

Builds on

14 of 31 references.

References · 14

  1. 2017Attention Is All You Needcited by 59,932
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  4. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  5. 2019Publicly Available Clinical BERT Embeddingscited by 995
  6. 2021Tabular Data: Deep Learning is Not All You Needcited by 530
  7. 2015Doctor AI: Predicting Clinical Events via Recurrent Neural Networkscited by 205
  8. 2024Large Language Models for Disease Diagnosis: A Scoping Reviewcited by 51
  9. 2025Clinical ModernBERT: An efficient and long context encoder for biomedical textcited by 26
  10. 2024Emergency Department Decision Support using Clinical Pseudo-notescited by 22
  11. 2022Artificial Intelligence-Based Methods for Fusion of Electronic Health Records and Imaging Datacited by 18
  12. 2025A Case Study Exploring the Current Landscape of Synthetic Medical Record Generation with Commercial LLMscited by 13
2 more
  1. 2018Generalizability of predictive models for intensive care unit patientscited by 9
  2. 2024FEET: A Framework for Evaluating Embedding Techniquescited by 8

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 7.

7 papers.

  1. 2026Learning Clinical Representations Under Systematic Distribution Shiftcited by 2
  2. 2026Discriminative Representation Learning for Clinical Predictioncited by 2
  3. 2026Learning Longitudinal Health Representations from EHR and Wearable Datacited by 1
  4. 2026Uncertainty-Aware Foundation Models for Clinical Datacited by 1
  5. 2026Event Fields: Learning Latent Event Structure for Waveform Foundation Modelscited by 0
  6. 2026WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Recordscited by 0
  7. 2026AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Modelscited by 0