AIMC Topic: Aged, 80 and over
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Urban and rural disparities in stroke prediction using machine learning among Chinese older adults.
Scientific reports
Feb 25, 2025
Stroke is a significant health concern in China. Differences in stroke risk between rural and urban areas have been highlighted in prior research. However, there is a scarcity of studies on urban-rural differences in predicting stroke. This study aim...
Predicting 90-day risk of urinary tract infections following urostomy in bladder cancer patients using machine learning and explainability.
Scientific reports
Feb 25, 2025
This research aims to design and validate a machine learning model to predict the probability of urinary tract infections within 90 days post-urostomy in bladder cancer patients. Clinical and follow-up information from 317 patients who had urostomy p...
Real-World Insights Into Dementia Diagnosis Trajectory and Clinical Practice Patterns Unveiled by Natural Language Processing: Development and Usability Study.
JMIR aging
Feb 25, 2025
BACKGROUND: Understanding the dementia disease trajectory and clinical practice patterns in outpatient settings is vital for effective management. Knowledge about the path from initial memory loss complaints to dementia diagnosis remains limited.
Deep Learning-Enhanced Ultra-high-resolution CT Imaging for Superior Temporal Bone Visualization.
Academic radiology
Feb 24, 2025
RATIONALE AND OBJECTIVES: This study assesses the image quality of temporal bone ultra-high-resolution (UHR) Computed tomography (CT) scans in adults and children using hybrid iterative reconstruction (HIR) and a novel, vendor-specific deep learning-...
Deep learning to quantify the pace of brain aging in relation to neurocognitive changes.
Proceedings of the National Academy of Sciences of the United States of America
Feb 24, 2025
Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroanatomic aging in cognitively normal (CN) individuals. BA, however, is a cross-sectional measure that summarizes cumulative neuroanatomic aging since bi...
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...
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