ArticleProceedings. IEEE International Symposium on Bioinformatics and Bioengineering2017
Delirium Prediction using Machine Learning Models on Preoperative Electronic Health Records Data.
Article in Proceedings. IEEE International Symposium on Bioinformatics and Bioengineering, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 3 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
35 citing papers in PubMed, 3 syntheses or guidelines pooled it, 53 citations in OpenAlex.
- Prediction Models for In-Hospital Delirium Using Routinely Collected Electronic Health Record Data: Systematic Review.JMIR medical informatics · 2026Pooled it
- Machine learning models for predicting postoperative delirium in non-cardiac surgery patients - systematic review and meta-analysis.GeroScience · 2026Pooled it
- The effect of non-pharmacologic strategies on prevention or management of intensive care unit delirium: a systematic review.F1000Research · 2020Pooled it
- Artificial Intelligence-Based Delirium Prediction Model for Post-Cardiac Surgery Patients: A Scoping Review.Journal of advanced nursing · 2026Article
- A large language model for delirium prediction in the intensive care unit using structured electronic health records.Scientific reports · 2025Article
- Predicting ICU Delirium in Critically Ill COVID-19 Patients Using Demographic, Clinical, and Laboratory Admission Data: A Machine Learning Approach.Life (Basel, Switzerland) · 2025Article
- Determining the ground truth for the prediction of delirium in adult patients in acute care: a scoping review.JAMIA open · 2025Review
- Machine Learning Multimodal Model for Delirium Risk Stratification.JAMA network open · 2025Article
- Development of a Disease Model for Predicting Postoperative Delirium Using Combined Blood Biomarkers.Annals of clinical and translational neurology · 2025Article
- Development and Validation of a Routine Electronic Health Record-Based Delirium Prediction Model for Surgical Patients Without Dementia: Retrospective Case-Control Study.JMIR perioperative medicine · 2025Article
- Applying a transformer architecture to intraoperative temporal dynamics improves the prediction of postoperative delirium.Communications medicine · 2024Article
- Novel opportunities for clinical pharmacy research: development of a machine learning model to identify medication related causes of delirium in different patient groups.International journal of clinical pharmacy · 2024Article
- Predicting postoperative delirium assessed by the Nursing Screening Delirium Scale in the recovery room for non-cardiac surgeries without craniotomy: A retrospective study using a machine learning approach.PLOS digital health · 2024Article
- Using Machine Learning and Electronic Health Records to Identify Neuropsychiatric Risk Scores for Delirium in ICU and General Hospital Settings.Neuropsychiatric disease and treatment · 2024Article
- Characterizing medical patients with delirium: A cohort study comparing ICD-10 codes and a validated chart review method.PloS one · 2024Article
- Temporal Generalizability of Machine Learning Models for Predicting Postoperative Delirium Using Electronic Health Record Data: Model Development and Validation Study.JMIR perioperative medicine · 2023Article
- Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics · 2023Article
- External validity of an automated delirium prediction model (DEMO) and comparison to the manual VMS-questions: a retrospective cohort study.International journal of clinical pharmacy · 2023Article
- Navigating the machine learning pipeline: a scoping review of inpatient delirium prediction models.BMJ health & care informatics · 2023Article
- Prediction of Prednisolone Dose Correction Using Machine Learning.Journal of healthcare informatics research · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
Electronic Health Records (EHR) are mainly designed to record relevant patient information during their stay in the hospital for administrative purposes. They additionally provide an efficient and inexpensive source of data for medical research, such as patient outcome prediction. In this study, we used preoperative Electronic Health Records to predict postoperative delirium. We compared the performance of seven machine learning models on delirium prediction: linear models, generalized additive models, random forests, support vector machine, neural networks, and extreme gradient boosting. Among the models evaluated in this study, random forests and generalized additive model outperformed the other models in terms of the overall performance metrics for prediction of delirium, particularly with respect to sensitivity. We found that age, alcohol or drug abuse, socioeconomic status, underlying medical issue, severity of medical problem, and attending surgeon can affect the risk of delirium.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.