AIMC Topic: Delirium
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Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients.
BMC surgery
Jan 15, 2025
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.
Application of machine learning for delirium prediction and analysis of associated factors in hospitalized COVID-19 patients: A comparative study using the Korean Multidisciplinary cohort for delirium prevention (KoMCoDe).
International journal of medical informatics
Dec 1, 2024
BACKGROUND: The incidence of delirium in hospitalized coronavirus disease 2019 (COVID-19) patients is linked to adverse health outcomes. Predicting the occurrence and risk factors of delirium is key to preventing its sudden onset.
Machine Learning for Prediction of Postoperative Delirium in Adult Patients: A Systematic Review and Meta-analysis.
Clinical therapeutics
Oct 11, 2024
PURPOSE: This meta-analysis aimed to evaluate the performance of machine learning (ML) models in predicting postoperative delirium (POD) and to provide guidance for clinical application.
Adopting machine learning to predict ICU delirium.
Neurosurgical review
Jul 26, 2024
With neuropsychiatric complications recognized among COVID-19 patients translating into significant morbidity, we explore the current state-of-the-art for auto Machine Learning (ML) to predict ICU delirium among severe COVID-19 patients which has bee...
Machine learning for the prediction of delirium in elderly intensive care unit patients.
European geriatric medicine
Jun 28, 2024
PURPOSE: This study aims to develop and validate a prediction model for delirium in elderly ICU patients and help clinicians identify high-risk patients at the early stage.
Machine learning-based model to predict delirium in patients with advanced cancer treated with palliative care: a multicenter, patient-based registry cohort.
Scientific reports
May 20, 2024
This study aimed to present a new approach to predict to delirium admitted to the acute palliative care unit. To achieve this, this study employed machine learning model to predict delirium in patients in palliative care and identified the significan...
Development and validation of a machine learning model to predict postoperative delirium using a nationwide database: A retrospective, observational study.
Journal of clinical anesthesia
Apr 27, 2024
STUDY OBJECTIVE: Postoperative delirium is a neuropsychological syndrome that typically occurs in surgical patients. Its onset can lead to prolonged hospitalization as well as increased morbidity and mortality. Therefore, it is important to promptly ...
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
Apr 9, 2024
The advent of artificial intelligence (AI) technologies has taken the world of science by storm in 2023. The opportunities of this easy to access technology for clinical pharmacy research are yet to be fully understood. The development of a custom-ma...
Machine learning methods for developing a predictive model of the incidence of delirium in cardiac intensive care units.
Revista espanola de cardiologia (English ed.)
Jan 16, 2024
INTRODUCTION AND OBJECTIVES: Delirium, recognized as a crucial prognostic factor in the cardiac intensive care unit (CICU), has evolved in response to the changing demographics among critically ill cardiac patients. This study aimed to create a predi...
Preoperative Delirium Risk Screening in Patients Undergoing a Cardiac Surgery: Results from the Prospective Observational FINDERI Study.
The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry
Dec 29, 2023
OBJECTIVE: Postoperative delirium (POD) is a common complication of cardiac surgery that is associated with higher morbidity, longer hospital stay, cognitive decline, and mortality. Preoperative assessments may help to identify patients´ POD risk. Ho...
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