AIMC Topic: Aged, 80 and over
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Cognitive performance classification of older patients using machine learning and electronic medical records.
Scientific reports
Feb 24, 2025
Dementia rates are projected to increase significantly by 2050, posing considerable challenges for healthcare systems worldwide. Developing efficient diagnostic tools is critical, and machine learning (ML) algorithms have shown potential for improvin...
Enhancing readmission prediction model in older stroke patients by integrating insight from readiness for hospital discharge: Prospective cohort study.
International journal of medical informatics
Feb 22, 2025
BACKGROUND: The 30-day hospital readmission rate is a key indicator of healthcare quality and system efficiency. This study aimed to develop machine-learning (ML) models to predict unplanned 30-day readmissions in older patients with ischemic stroke ...
Machine learning based on nutritional assessment to predict adverse events in older inpatients with possible sarcopenia.
Aging clinical and experimental research
Feb 22, 2025
BACKGROUND: The accuracy of current tools for predicting adverse events in older inpatients with possible sarcopenia is still insufficient to develop individualized nutrition-related management strategies. The objectives were to develop a machine lea...
Biophysical versus machine learning models for predicting rectal and skin temperatures in older adults.
Journal of thermal biology
Feb 22, 2025
This study compares the efficacy of machine learning models to traditional biophysical models in predicting rectal (T) and skin (T) temperatures of older adults (≥60 years) during prolonged heat exposure. Five machine learning models were trained on ...
Utilizing 12-lead electrocardiogram and machine learning to retrospectively estimate and prospectively predict atrial fibrillation and stroke risk.
Computers in biology and medicine
Feb 21, 2025
BACKGROUND: The stroke risk in patients with subclinical atrial fibrillation (AF) is underestimated. By identifying patients at high risk of embolic stroke, health-care professionals can make more informed decisions regarding anticoagulation treatmen...
An Integrative Machine Learning Model for Predicting Early Safety Outcomes in Patients Undergoing Transcatheter Aortic Valve Implantation.
Medicina (Kaunas, Lithuania)
Feb 21, 2025
: Early safety outcomes following transcatheter aortic valve implantation (TAVI) for severe aortic stenosis are critical for patient prognosis. Accurate prediction of adverse events can enhance patient management and improve outcomes. : This study ai...
New machine-learning models outperform conventional risk assessment tools in Gastrointestinal bleeding.
Scientific reports
Feb 21, 2025
Rapid and accurate identification of high-risk acute gastrointestinal bleeding (GIB) patients is essential. We developed two machine-learning (ML) models to calculate the risk of in-hospital mortality in patients admitted due to overt GIB. We analyze...
Early prediction of 30-day mortality in patients with surgical wound infections following cardiothoracic surgery: Development and validation of the SWICS-30 score utilizing conventional logistic regression and artificial neural network.
The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases
Feb 21, 2025
INTRODUCTION: We aimed to create and validate the 30-day prognostic score for mortality in patients with surgical wound infection (SWICS-30) after cardiothoracic surgery.
T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.
Journal of applied clinical medical physics
Feb 20, 2025
PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Personalised screening tool for early detection of sarcopenia in stroke patients: a machine learning-based comparative study.
Aging clinical and experimental research
Feb 20, 2025
BACKGROUND: Sarcopenia is a common complication in patients with stroke, adversely affecting recovery and increasing mortality risk. However, no standardised tool exists for its screening in this population. This study aims to identify factors influe...
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