mlsanityData to 7 Oct 2026

Using Clinical Notes with Time Series Data for ICU Management

arXiv 1909.09702 ↗First posted 12 Sep 2019cs.CL cs.LG stat.MLcited by 38

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Abstract (arXiv)

Monitoring patients in ICU is a challenging and high-cost task. Hence, predicting the condition of patients during their ICU stay can help provide better acute care and plan the hospital's resources. There has been continuous progress in machine learning research for ICU management, and most of this work has focused on using time series signals recorded by ICU instruments. In our work, we show that adding clinical notes as another modality improves the performance of the model for three benchmark tasks: in-hospital mortality prediction, modeling decompensation, and length of stay forecasting that play an important role in ICU management. While the time-series data is measured at regular intervals, doctor notes are charted at irregular times, making it challenging to model them together. We propose a method to model them jointly, achieving considerable improvement across benchmark tasks over baseline time-series model. Our implementation can be found at urlhttps://github.com/kaggarwal/ClinicalNotesICU.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Sep 2019.

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Citing papers per year: 2021: 3; 2022: 5; 2023: 9; 2024: 9; 2025: 6; 2026: 6.

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  1. 2024FuseMoE: Mixture-of-Experts Transformers for Fleximodal Fusioncited by 67
  2. 2022A Multimodal Transformer: Fusing Clinical Notes with Structured EHR Data for Interpretable In-Hospital Mortality Predictioncited by 48
  3. 2021Clinical Outcome Prediction from Admission Notes using Self-Supervised Knowledge Integrationcited by 43
  4. 2022Improving Medical Predictions by Irregular Multimodal Electronic Health Records Modelingcited by 33
  5. 2025Multi-modal Time Series Analysis: A Tutorial and Surveycited by 24
  6. 2024REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Modelscited by 21
  7. 2024EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generationcited by 16
  8. 2022Multimodal data matters: language model pre-training over structured and unstructured electronic health recordscited by 13
  9. 2022On the Importance of Clinical Notes in Multi-modal Learning for EHR Datacited by 10
  10. 2023FineEHR: Refine Clinical Note Representations to Improve Mortality Predictioncited by 9
  11. 2021What Do You See in this Patient? Behavioral Testing of Clinical NLP Modelscited by 6
  12. 2023MedLens: Improve Mortality Prediction Via Medical Signs Selecting and Regressioncited by 6
26 more
  1. 2024CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysiscited by 6
  2. 2023On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Seriescited by 5
  3. 2024Next Visit Diagnosis Prediction via Medical Code-Centric Multimodal Contrastive EHR Modelling with Hierarchical Regularisationcited by 5
  4. 2024BadCLM: Backdoor Attack in Clinical Language Models for Electronic Health Recordscited by 5
  5. 2025Massively Multimodal Foundation Models: A Framework for Capturing Interactions with Specialized Mixture-of-Expertscited by 4
  6. 2023Knowledge Graph Representations to enhance Intensive Care Time-Series Predictionscited by 3
  7. 2025Benchmarking and Improving LVLMs on Event Extraction from Multimedia Documentscited by 3
  8. 2023MVMTnet: A Multi-variate Multi-modal Transformer for Multi-class Classification of Cardiac Irregularities Using ECG Waveforms and Clinical Notescited by 2
  9. 2023Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learningcited by 2
  10. 2023Multi-modal Graph Learning over UMLS Knowledge Graphscited by 2
  11. 2024Contrastive Learning on Multimodal Analysis of Electronic Health Recordscited by 2
  12. 2024Multi-Modal Contrastive Learning for Online Clinical Time-Series Applicationscited by 2
  13. 2026MILM: Large Language Models for Multimodal Irregular Time Series with Informative Samplingcited by 2
  14. 2021Using Clinical Drug Representations for Improving Mortality and Length of Stay Predictionscited by 1
  15. 2024LETS-C: Leveraging Text Embedding for Time Series Classificationcited by 1
  16. 2025CURENet: Combining Unified Representations for Efficient Chronic Disease Predictioncited by 1
  17. 2025Transparent Early ICU Mortality Prediction with Clinical Transformer and Per-Case Modality Attributioncited by 1
  18. 2022Natural Language Processing Methods to Identify Oncology Patients at High Risk for Acute Care with Clinical Notescited by 0
  19. 2023Length of Stay prediction for Hospital Management using Domain Adaptationcited by 0
  20. 2023XAI for In-hospital Mortality Prediction via Multimodal ICU Datacited by 0
  21. 2025Integrating Text and Time-Series into (Large) Language Models to Predict Medical Outcomescited by 0
  22. 2026Temporal Fusion Nexus: A task-agnostic multi-modal embedding model for clinical narratives and irregular time series in post-kidney transplant carecited by 0
  23. 2026A Clinical Point Cloud Paradigm for In-Hospital Mortality Prediction from Multi-Level Incomplete Multimodal EHRscited by 0
  24. 2026Large Language Models as Unified Multimodal Learners for Clinical Predictioncited by 0
  25. 2026Backdoor Learning in Language Models and Vision-Language Modelscited by 0
  26. 2026NeuroECG: ECGFounder-Based Deep ECG Representation for EEG-Free Neurological Prognostication After Cardiac Arrestcited by 0