AIMC Topic: Aged, 80 and over
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Machine learning-based diagnostic model for stroke in non-neurological intensive care unit patients with acute neurological manifestations.
Scientific reports
Nov 28, 2024
Stroke is a neurological complication that can occur in patients admitted to the intensive care unit (ICU) for non-neurological conditions, leading to increased mortality and prolonged hospital stays. The incidence of stroke in ICU settings is notabl...
Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Nov 27, 2024
INTRODUCTION: Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover sy...
Predicting executive functioning from walking features in Parkinson's disease using machine learning.
Scientific reports
Nov 27, 2024
Parkinson's disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and ...
Screening for frequent hospitalization risk among community-dwelling older adult between 2016 and 2023: machine learning-driven item selection, scoring system development, and prospective validation.
Frontiers in public health
Nov 27, 2024
BACKGROUND: Screening for frequent hospitalizations in the community can help prevent super-utilizers from growing in the inpatient population. However, the determinants of frequent hospitalizations have not been systematically examined, their operat...
Evaluating the reproducibility of a deep learning algorithm for the prediction of retinal age.
GeroScience
Nov 26, 2024
Recently, a deep learning algorithm (DLA) has been developed to predict the chronological age from retinal images. The Retinal Age Gap (RAG), a deviation between predicted age from retinal images (Retinal Age, RA) and chronological age, correlates wi...
A Study on Automatic O-RADS Classification of Sonograms of Ovarian Adnexal Lesions Based on Deep Convolutional Neural Networks.
Ultrasound in medicine & biology
Nov 26, 2024
OBJECTIVE: This study explored a new method for automatic O-RADS classification of sonograms based on a deep convolutional neural network (DCNN).
American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.
Surgery
Nov 26, 2024
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...
Machine learning insights on activities of daily living disorders in Chinese older adults.
Experimental gerontology
Nov 26, 2024
OBJECTIVE: This study on the aged population in China first used a large-scale longitudinal survey database to explore how different life factors affect their ability to engage in daily activities. We select and integrate multiple machine models to o...
Prognostic value of glycaemic variability for mortality in critically ill atrial fibrillation patients and mortality prediction model using machine learning.
Cardiovascular diabetology
Nov 26, 2024
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
Blood Glucose
Time Factors
Hospital Mortality
Predictive Value of Tests
Cause of Death
Aged, 80 and over
Male
Middle Aged
Risk Assessment
Atrial Fibrillation
Glycemic Control
Biomarkers
Prognosis
Retrospective Studies
Critical Illness
Intensive Care Units
Female
Reproducibility of Results
Risk Factors
Aged
Humans
Machine Learning
Decision Support Techniques
Databases, Factual
Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.
Lipids in health and disease
Nov 26, 2024
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...
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