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.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039025
Patients in the ICU frequently suffer from delirium, which can delay their recovery and may cause significant distress. Despite standardized scoring systems, its diagnosis and classification however, remain largely subjective and are subject to intra...
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...
International journal of medical informatics
39644794
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.
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.
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.
Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society
39814058
BACKGROUND: Postoperative delirium (POD) poses significant clinical challenges regarding its diagnosis and treatment. Identifying biomarkers that can predict and diagnose POD is crucial for improving patient outcomes.
STUDY OBJECTIVE: Delirium is a common complication after cardiac surgery and is associated with poor prognosis. An effective delirium prediction model could identify high-risk patients who might benefit from targeted prevention strategies. We introdu...
BACKGROUND: The incidence of delirium in patients with burns receiving treatment in the intensive care unit (ICU) is high, reaching up to 77%, and has been associated with increased mortality rates. Therefore, early identification of patients at high...
BACKGROUND: Delirium is common in hospitalized patients and is correlated with increased morbidity and mortality. Despite this, delirium is underdiagnosed, and many institutions do not have sufficient resources to consistently apply effective screeni...