AIMC Topic: Length of Stay
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Development and external validation of an interpretable machine learning model for the prediction of intubation in the intensive care unit.
Scientific reports
Nov 8, 2024
Given the limited capacity to accurately determine the necessity for intubation in intensive care unit settings, this study aimed to develop and externally validate an interpretable machine learning model capable of predicting the need for intubation...
Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data.
PloS one
Oct 29, 2024
OBJECTIVES: The primary objective of this study was to identify clinical and socioeconomic predictors of hospital and ED use among children with medical complexity within 1 and 5 years of an initial discharge between 2010 and 2013. A secondary object...
One-year employment outcome prediction after traumatic brain injury: A CENTER-TBI study.
Disability and health journal
Oct 10, 2024
BACKGROUND: Traumatic brain injury (TBI) can come with long term consequences for functional outcome that can complicate return to work.
Machine Learning Model for Predicting Risk Factors of Prolonged Length of Hospital Stay in Patients with Aortic Dissection: a Retrospective Clinical Study.
Journal of cardiovascular translational research
Oct 10, 2024
The length of hospital stay (LOS) is crucial for assessing medical service quality. This study aimed to develop machine learning models for predicting risk factors of prolonged LOS in patients with aortic dissection (AD). The data of 516 AD patients ...
Using novel machine learning tools to predict optimal discharge following transcatheter aortic valve replacement.
Archives of cardiovascular diseases
Oct 5, 2024
BACKGROUND: Although transcatheter aortic valve replacement has emerged as an alternative to surgical aortic valve replacement, it requires extensive healthcare resources, and optimal length of hospital stay has become increasingly important. This st...
Female
Risk Factors
Aged
Aged, 80 and over
Decision Support Techniques
Databases, Factual
Retrospective Studies
Clinical Decision-Making
United States
Treatment Outcome
Aortic Valve Stenosis
Aortic Valve
Predictive Value of Tests
Male
Risk Assessment
Length of Stay
Time Factors
Humans
Neural Networks, Computer
Machine Learning
Patient Discharge
Transcatheter Aortic Valve Replacement
Machine learning-augmented interventions in perioperative care: a systematic review and meta-analysis.
British journal of anaesthesia
Sep 24, 2024
BACKGROUND: We lack evidence on the cumulative effectiveness of machine learning (ML)-driven interventions in perioperative settings. Therefore, we conducted a systematic review to appraise the evidence on the impact of ML-driven interventions on per...
Predicting extended hospital stay following revision total hip arthroplasty: a machine learning model analysis based on the ACS-NSQIP database.
Archives of orthopaedic and trauma surgery
Sep 19, 2024
INTRODUCTION: Prolonged length of stay (LOS) following revision total hip arthroplasty (THA) can lead to increased healthcare costs, higher rates of readmission, and lower patient satisfaction. In this study, we investigated the predictive power of m...
Predicting prolonged length of stay following revision total knee arthroplasty: A national database analysis using machine learning models.
International journal of medical informatics
Sep 18, 2024
BACKGROUND: As the number of revision total knee arthroplasty (TKA) continues to rise, close attention has been paid to factors influencing postoperative length of stay (LOS). The aim of this study is to develop generalizable machine learning (ML) al...
Quality of birth care and risk factors of length of stay after birth: A machine learning approach.
The journal of obstetrics and gynaecology research
Sep 16, 2024
AIM: Length of stay (LOS) is an outcome measure and is assumed to be related to quality. The objective of this study is to examine the quality of birth care and risk factors associated with LOS after birth.
Development of a machine learning model to estimate length of stay in coronary artery bypass grafting.
Revista de saude publica
Sep 16, 2024
OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.
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