mlsanityData to 14 Oct 2026

ChronoFormer: Time-Aware Transformer Architectures for Structured Clinical Event Modeling

arXiv 2504.07373 ↗First posted 10 Apr 2025cs.LG cs.AIcited by 12

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Abstract (arXiv)

The temporal complexity of electronic health record (EHR) data presents significant challenges for predicting clinical outcomes using machine learning. This paper proposes ChronoFormer, an innovative transformer based architecture specifically designed to encode and leverage temporal dependencies in longitudinal patient data. ChronoFormer integrates temporal embeddings, hierarchical attention mechanisms, and domain specific masking techniques. Extensive experiments conducted on three benchmark tasks mortality prediction, readmission prediction, and long term comorbidity onset demonstrate substantial improvements over current state of the art methods. Furthermore, detailed analyses of attention patterns underscore ChronoFormer's capability to capture clinically meaningful long range temporal relationships.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 21 of its 30 references that are in the map. First posted on arXiv 10 Apr 2025.

Builds on

21 of 30 references.

References · 21

  1. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
  2. 2019Publicly Available Clinical BERT Embeddingscited by 1,002
  3. 2020Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease predictioncited by 373
  4. 2016RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanismcited by 349
  5. 2022TabLLM: Few-shot Classification of Tabular Data with Large Language Modelscited by 277
  6. 2019BEHRT: Transformer for Electronic Health Recordscited by 263
  7. 2017Gate-Variants of Gated Recurrent Unit (GRU) Neural Networkscited by 242
  8. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  9. 2017Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysiscited by 148
  10. 2022Should You Mask 15% in Masked Language Modeling?cited by 118
  11. 2020Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Datacited by 87
  12. 2021CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction taskscited by 76
9 more
  1. 2021Hi-BEHRT: Hierarchical Transformer-based model for accurate prediction of clinical events using multimodal longitudinal electronic health recordscited by 54
  2. 2025Large Language Models are Powerful Electronic Health Record Encoderscited by 26
  3. 2025Clinical ModernBERT: An efficient and long context encoder for biomedical textcited by 26
  4. 2019TAPER: Time-Aware Patient EHR Representationcited by 22
  5. 2024Emergency Department Decision Support using Clinical Pseudo-notescited by 22
  6. 2024Can Large Language Models abstract Medical Coded Language?cited by 20
  7. 2024Text Serialization and Their Relationship with the Conventional Paradigms of Tabular Machine Learningcited by 17
  8. 2024When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation for Medical Machine Learning Applications?cited by 12
  9. 2024Predictive Modeling with Temporal Graphical Representation on Electronic Health Recordscited by 9

Built on by

Cited by year (2026 to 14 Oct)

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

12 papers.

  1. 2026A multimodal and temporal foundation model for virtual patient representations at healthcare system scalecited by 8
  2. 2025Deep Learning Approach for Clinical Risk Identification Using Transformer Modeling of Heterogeneous EHR Datacited by 5
  3. 2026Learning Clinical Representations Under Systematic Distribution Shiftcited by 2
  4. 2026Discriminative Representation Learning for Clinical Predictioncited by 2
  5. 2026Learning Longitudinal Health Representations from EHR and Wearable Datacited by 1
  6. 2026Uncertainty-Aware Foundation Models for Clinical Datacited by 1
  7. 2026A-THENA: Early Intrusion Detection for IoT with Time-Aware Hybrid Encoding and Network-Specific Augmentationcited by 1
  8. 2026Uncertainty-Aware Longitudinal Forecasting of Alzheimer's Disease Progression Using Deep Learningcited by 1
  9. 2026Event Fields: Learning Latent Event Structure for Waveform Foundation Modelscited by 0
  10. 2026WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Recordscited by 0
  11. 2026AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Modelscited by 0
  12. 2026MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveformscited by 0