This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (3229) Secondary Use of Clinical Data for Research and Surveillance (474) Natural Language Processing (917) Clinical Information and Decision Making (1914) Decision Support for Health Professionals (1538) Electronic Health Records (1319)

Published on in Vol 6, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/33834, first published .
Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study

Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study

Identifying Patients With Delirium Based on Unstructured Clinical Notes: Observational Study

Authors of this article:

Wendong Ge1 Author Orcid Image ;   Haitham Alabsi1 Author Orcid Image ;   Aayushee Jain1 Author Orcid Image ;   Elissa Ye1 Author Orcid Image ;   Haoqi Sun1 Author Orcid Image ;   Marta Fernandes1 Author Orcid Image ;   Colin Magdamo1 Author Orcid Image ;   Ryan A Tesh1 Author Orcid Image ;   Sarah I Collens1 Author Orcid Image ;   Amy Newhouse1 Author Orcid Image ;   Lidia MVR Moura1 Author Orcid Image ;   Sahar Zafar1 Author Orcid Image ;   John Hsu1 Author Orcid Image ;   Oluwaseun Akeju1 Author Orcid Image ;   Gregory K Robbins1 Author Orcid Image ;   Shibani S Mukerji1 Author Orcid Image ;   Sudeshna Das1 Author Orcid Image ;   M Brandon Westover1 Author Orcid Image
Article Authors Cited by (15) Tweetations (4) Metrics

Journals

  1. Qu J, Mueller A, McKay T, Westover M, Shelton K, Shaefi S, D'Alessandro D, Berra L, Brown E, Houle T, Akeju O. Nighttime dexmedetomidine for delirium prevention in non-mechanically ventilated patients after cardiac surgery (MINDDS): a single-centre, parallel-arm, randomised, placebo-controlled superiority trial. eClinicalMedicine 2023;56:101796 View
  2. Ser S, Shear K, Snigurska U, Prosperi M, Wu Y, Magoc T, Bjarnadottir R, Lucero R. Clinical Prediction Models for Hospital-Induced Delirium Using Structured and Unstructured Electronic Health Record Data: Protocol for a Development and Validation Study. JMIR Research Protocols 2023;12:e48521 View
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  4. Miyazawa Y, Katsuta N, Nara T, Nojiri S, Naito T, Hiki M, Ichikawa M, Takeshita Y, Kato T, Okumura M, Tobita M, Jakovljevic M. Identification of risk factors for the onset of delirium associated with COVID-19 by mining nursing records. PLOS ONE 2024;19(1):e0296760 View
  5. Amjad S, Holmes N, Kishore K, Young M, Bailey J, Bellomo R, Verspoor K. Advancing delirium classification: A clinical notes-based natural language processing-supported machine learning model. Intelligence-Based Medicine 2024;9:100140 View
  6. Osman M, Cooper R, Sayer A, Witham M. The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review. Age and Ageing 2024;53(7) View
  7. Devlin J, Sieber F, Akeju O, Khan B, MacLullich A, Marcantonio E, Oh E, Agar M, Avelino-Silva T, Berger M, Burry L, Colantuoni E, Evered L, Girard T, Han J, Hosie A, Hughes C, Jones R, Pandharipande P, Subramanian B, Travison T, van den Boogaard M, Inouye S. Advancing Delirium Treatment Trials in Older Adults: Recommendations for Future Trials From the Network for Investigation of Delirium: Unifying Scientists (NIDUS). Critical Care Medicine 2025;53(1):e15 View
  8. Xu Y, Min M, Tan L. Regarding: the interplay of delirium and frailty in hospitalized older adults. Journal of Internal Medicine 2025;297(4):448 View
  9. Lv S, Li J, He H, Zhao Q, Jiang Y. Artificial intelligence applications in delirium prediction, diagnosis, and management: a systematic review. Artificial Intelligence Review 2025;58(9) View
  10. Miguel C, Santos Bittencourt J, Tavares L, Vidra B, Gazzola M, Pinheiro da Costa Rozzino T, Avelino-Silva T, Szlejf C. Developing the CAM-BERT: Enhancing delirium screening in hospitalized older adults using natural language processing. Computers in Biology and Medicine 2025;196:110781 View
  11. Singh A, Sartipi S, Sun H, Milde R, Turley N, Quinn C, Harrold G, Gillani R, Turbett S, Das S, Zafar S, Fernandes M, Westover M, Mukerji S. A Machine Learning Approach for Identifying People With Neuroinfectious Diseases in Electronic Health Records: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e63157 View
  12. Shankar R, Kannan J, Tan Y, Xu Q. Natural language processing techniques to detect delirium in hospitalized patients from clinical notes: a systematic review. npj Digital Medicine 2025;8(1) View

Books/Policy Documents

  1. Guellil I, Andres S, Guthrie B, Anand A, Zhang H, Hasan A, Wu H, Alex B. Natural Language Processing and Information Systems. View

Conference Proceedings

  1. Chen A, Paredes D, Yu Z, Lou X, Brunson R, Thomas J, Martinez K, Lucero R, Magoc T, Solberg L, Snigurska U, Ser S, Prosperi M, Bian J, Bjarnadottir R, Wu Y. 2024 IEEE 12th International Conference on Healthcare Informatics (ICHI). Identifying Symptoms of Delirium from Clinical Narratives Using Natural Language Processing View
  2. Lv S, Li J, Ouyang Y, Qi H, Jiang Y, Zhao Q. 2025 IEEE 49th Annual Computers, Software, and Applications Conference (COMPSAC). A Contrastive Learning and Region-Guided Approach for Long Clinical Text Classification View