2000 character limit reached
Continuous Predictive Modeling of Clinical Notes and ICD Codes in Patient Health Records (2405.11622v2)
Published 19 May 2024 in cs.CL and cs.LG
Abstract: Electronic Health Records (EHR) serve as a valuable source of patient information, offering insights into medical histories, treatments, and outcomes. Previous research has developed systems for detecting applicable ICD codes that should be assigned while writing a given EHR document, mainly focusing on discharge summaries written at the end of a hospital stay. In this work, we investigate the potential of predicting these codes for the whole patient stay at different time points during their stay, even before they are officially assigned by clinicians. The development of methods to predict diagnoses and treatments earlier in advance could open opportunities for predictive medicine, such as identifying disease risks sooner, suggesting treatments, and optimizing resource allocation. Our experiments show that predictions regarding final ICD codes can be made already two days after admission and we propose a custom model that improves performance on this early prediction task.
- Understanding patient needs and gaps in radiology reports through online discussion forum analysis. Insights Imaging, 12(50).
- Longformer: The long-document transformer. CoRR, abs/2004.05150.
- Donna J Cartwright. 2013. Icd-9-cm to icd-10-cm codes: What? why? how? Advances in Wound Care, 2(10):588–592.
- MDACE: MIMIC documents annotated with code evidence. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 7534–7550, Toronto, Canada. Association for Computational Linguistics.
- From block-toeplitz matrices to differential equations on graphs: towards a general theory for scalable masked transformers. In International Conference on Machine Learning.
- Revisiting transformer-based models for long document classification. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 7212–7230, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
- Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. ACM transactions on computing for healthcare, 3(1):1–23.
- ClinicalBERT: modeling clinical notes and predicting hospital readmission. Computing Research Repository, arXiv:1904.05342v3. Version 3.
- Mining electronic health records: towards better research applications and clinical care. Nature Reviews Genetics, 13(6):395–405.
- Does the magic of bert apply to medical code assignment? a quantitative study. Computers in Biology and Medicine, 139:104998.
- MIMIC-III, a freely accessible critical care database. Scientific Data, 3(160035).
- Haanju Yoo Daeseong Kim Sewon Kim. 2022. An Automatic ICD Coding Network Using Partition-Based Label Attention . SSRN Electronic Journal.
- Pretrained language models for biomedical and clinical tasks: understanding and extending the state-of-the-art. Proceedings of the 3rd Clinical Natural Language Processing Workshop, page 146.
- Fei Li and Hong Yu. 2020. ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network. Proceedings of the AAAI Conference on Artificial Intelligence, 34(05):8180.
- Hierarchical label-wise attention transformer model for explainable icd coding. Journal of biomedical informatics, 133:104161.
- Effective convolutional attention network for multi-label clinical document classification. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 5941–5953, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Efficient estimation of word representations in vector space. Proceedings of Workshop at ICLR, 2013.
- Explainable prediction of medical codes from clinical text. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 1101–1111, New Orleans, Louisiana. Association for Computational Linguistics.
- Leave no context behind: Efficient infinite context transformers with infini-attention. arXiv preprint arXiv:2404.07143.
- Modelling temporal document sequences for clinical ICD coding. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 1640–1649, Dubrovnik, Croatia. Association for Computational Linguistics.
- Leslie N Smith and Nicholay Topin. 2019. Very fast training of neural networks using large learning rate. Artificial intelligence and machine learning for multi-domain operations applications, 1106:369–386.
- Automated ICD coding via unsupervised knowledge integration (UNITE). International journal of medical informatics, 139, 104135.
- Challenges and opportunities beyond structured data in analysis of electronic health records. Wiley Interdisciplinary Reviews: Computational Statistics, 13(6):e1549.
- Echocardiography segmentation using neural ode-based diffeomorphic registration field. IEEE Transactions On Medical Imaging, XX.
- Attention is all you need. In Advances in Neural Information Processing Systems (NIPS).
- A label attention model for ICD coding from clinical text. In Proceedings of IJCAI. Doi:10.24963/ijcai.2020/461.
- Code synonyms do matter: Multiple synonyms matching network for automatic ICD coding. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 808–814, Dublin, Ireland. Association for Computational Linguistics.
- Mireia Hernandez Caralt (2 papers)
- Clarence Boon Liang Ng (3 papers)
- Marek Rei (52 papers)