Article

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care Unit

2026-02-23

Abstract excerpt

<title>Abstract</title> <p> <bold>Objective</bold> This study aimed to clarify the incidence and influencing factors of delirium in ICU patients after brain tumor surgery, construct and validate delirium risk prediction models using multiple machine learning algorithms, identify the optimal model, and develop a personalized risk calculation tool to provide evidence-based support for early precise identification...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: d5ccfc09-7b24-5856-b6a9-423825dafd95
DOI: 10.21203/rs.3.rs-8893713/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Development and validation of a machine learning-based model for predicting delirium risk in postoperative brain tumor patients in the Intensive Care UnitDOI 10.21203/rs.3.rs-8893713/v1Read

Development of a Machine Learning-Based Prediction Model for Postoperative Delirium in Frail Elderly Patients Undergoing Non-Cardiac Surgery Under General AnesthesiaSemantic proximity Read

Development and validation of a postoperative delirium risk prediction model for non-cardiac surgery in elderly patients: The PNDABLE StudySemantic proximity Read

Based on machine learning, which part of the perioperative period predicts postoperative delirium better? A retrospective case-control studySemantic proximity Read

Development of an Early Prediction Model for Postoperative Delirium in Neurosurgical Patients Admitted to the ICU after Elective Craniotomy (E-PREPOD-NS): A Secondary Analysis of A Prospective Cohort StudySemantic proximity Read

Development and internal validation of a gradient-boosted trees model for prediction of delirium after surgery and anesthesia (the BioCog study)Semantic proximity Read

Development and validation of a nomogram model for predicting postoperative delirium in older adults undergoing free flap reconstruction after oral cancer surgerySemantic proximity Read

Risk prediction models for delirium in ICU patients: A systematic review and critical appraisalSemantic proximity Read

Predicting postoperative delirium after hip arthroplasty for elderly patients using machine learningSemantic proximity Read

Development and validation a machine learning model based on clinical factors to predict short-term prognosis of ICU intracerebral hemorrhage patients: a retrospective studySemantic proximity Read

A Rolling-Window Framework for Dynamic Prediction of Delirium in Mechanically Ventilated ICU Patients: A Study Using MIMIC-IVSemantic proximity Read

The incidence of delirium in the elderly after surgery and risk factorsSemantic proximity Read

Association Between the Confusion Assessment Method for the Intensive Care Unit (CAM- ICU) and Prolonged Mechanical Ventilation Following Major Cardiac SurgerySemantic proximity Read