AIMC Topic: Aged

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Uncovering Predictors of Low Hippocampal Volume: Evidence from a Large-Scale Machine-Learning-Based Study in the UK Biobank.

Neuroepidemiology Apr 1, 2024
INTRODUCTION: Hippocampal atrophy is an established biomarker for conversion from the normal ageing process to developing cognitive impairment and dementia. This study used a novel hypothesis-free machine-learning approach, to uncover potential risk ...
Biological Specimen Banks Humans Aged Hippocampus Machine Learning United Kingdom Male Female Atrophy Middle Aged Risk Factors Magnetic Resonance Imaging UK Biobank
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Using Natural Language Processing to Identify Home Health Care Patients at Risk for Diagnosis of Alzheimer's Disease and Related Dementias.

Journal of applied gerontology : the official journal of the Southern Gerontological Society Mar 31, 2024
This study aimed to: (1) validate a natural language processing (NLP) system developed for the home health care setting to identify signs and symptoms of Alzheimer's disease and related dementias (ADRD) documented in clinicians' free-text notes; (2) ...
Humans Reproducibility of Results Aged Aged, 80 and over Medicare Datasets as Topic Proportional Hazards Models Male United States Longitudinal Studies Natural Language Processing
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Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T.

NMR in biomedicine Mar 31, 2024
OBJECTIVES: To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa).
Diffusion Magnetic Resonance Imaging Humans Machine Learning Aged Male Middle Aged ROC Curve Prostatic Neoplasms Motion
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Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

Health services research Mar 30, 2024
OBJECTIVE: To improve the performance of International Classification of Disease (ICD) code rule-based algorithms for identifying low acuity Emergency Department (ED) visits by using machine learning methods and additional covariates.
Age Factors Emergency Service, Hospital Patient Acuity Sex Factors International Classification of Diseases Emergency Room Visits Child, Preschool Child Logistic Models United States Humans Machine Learning Adult Male Algorithms Middle Aged Female Adolescent Aged Young Adult
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Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Mar 30, 2024
BACKGROUND: Although regional wall motion abnormality (RWMA) detection is foundational to transthoracic echocardiography, current methods are prone to interobserver variability. We aimed to develop a deep learning (DL) model for RWMA assessment and c...
Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Observer Variation Humans Aged Artificial Intelligence Male Female Echocardiography Reproducibility of Results Middle Aged Deep Learning
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Exploratory analysis using machine learning algorithms to predict pinch strength by anthropometric and socio-demographic features.

International journal of occupational safety and ergonomics : JOSE Mar 30, 2024
. This study examines the role of different machine learning (ML) algorithms to determine which socio-demographic factors and hand-forearm anthropometric dimensions can be used to accurately predict hand function. . The cross-sectional study was cond...
Adult Cross-Sectional Studies Male Middle Aged Adolescent Female Aged Aged, 80 and over Young Adult Anthropometry Forearm Pinch Strength Child Socioeconomic Factors Hand Iran Humans Machine Learning Algorithms
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Evaluating convolutional neural network-enhanced electrocardiography for hypertrophic cardiomyopathy detection in a specialized cardiovascular setting.

Heart and vessels Mar 30, 2024
The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting hypertrophic cardiomyopathy (HCM) and dilated HCM (dHCM) remains uncertain in real-world applications. This retrospective study analyzed data from 19,1...
Humans Neural Networks, Computer Male Middle Aged Electrocardiography Predictive Value of Tests Cardiomyopathy, Hypertrophic Retrospective Studies Female Aged Adult
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Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Mar 30, 2024
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and t...
Mitral Valve Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Automation Myocardial Ischemia Echocardiography, Doppler Blood Flow Velocity Diastole Middle Aged Magnetic Resonance Imaging, Cine Reproducibility of Results Deep Learning Humans Aged Chronic Disease Female Male Predictive Value of Tests Ventricular Function, Left
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Optimal Implant Sizing Using Machine Learning Is Associated With Increased Range of Motion After Cervical Disk Arthroplasty.

Neurosurgery Mar 29, 2024
BACKGROUND AND OBJECTIVES: Cervical disk arthroplasty (CDA) offers the advantage of motion preservation in the treatment of focal cervical pathology. At present, implant sizing is performed using subjective tactile feedback and imaging of trial cages...
Machine Learning Retrospective Studies Female Aged Adult Humans Cervical Vertebrae Male Range of Motion, Articular Middle Aged Intervertebral Disc Degeneration Treatment Outcome Arthroplasty Prostheses and Implants Intervertebral Disc
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Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

Journal of neurosurgery Mar 29, 2024
OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneurysmal subarachnoid hemorrhage (aSAH) remain uncertain. Here, the authors apply their recently devel...
Deep Learning Hydrocephalus Subarachnoid Hemorrhage Humans Aged Retrospective Studies Adult Tomography, X-Ray Computed Male Female Middle Aged Postoperative Complications
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