AIMC Topic: Aged

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Comparative diagnostic accuracy of ChatGPT-4 and machine learning in differentiating spinal tuberculosis and spinal tumors.

The spine journal : official journal of the North American Spine Society Jan 11, 2025
BACKGROUND: In clinical practice, distinguishing between spinal tuberculosis (STB) and spinal tumors (ST) poses a significant diagnostic challenge. The application of AI-driven large language models (LLMs) shows great potential for improving the accu...
Retrospective Studies Female Aged Young Adult Humans Machine Learning Algorithms Generative Artificial Intelligence Magnetic Resonance Imaging Diagnosis, Differential Spinal Neoplasms Tuberculosis, Spinal Adult Sensitivity and Specificity Male Middle Aged
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Generation of high-resolution MPRAGE-like images from 3D head MRI localizer (AutoAlign Head) images using a deep learning-based model.

Japanese journal of radiology Jan 11, 2025
PURPOSE: Magnetization prepared rapid gradient echo (MPRAGE) is a useful three-dimensional (3D) T1-weighted sequence, but is not a priority in routine brain examinations. We hypothesized that converting 3D MRI localizer (AutoAlign Head) images to MPR...
Retrospective Studies Female Aged Male Humans Magnetic Resonance Imaging Brain Cognitive Dysfunction Dementia Middle Aged Imaging, Three-Dimensional Deep Learning
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Service robots in caring for older adults: Uncovering the current conceptual and intellectual structures and future research agenda.

Archives of gerontology and geriatrics Jan 11, 2025
Service robots have supported human activity, mainly caring for older adults, for many years. However, a new generation of service robots empowered by artificial intelligence and other novel technologies indicates an increasing use of service robots ...
Humans Artificial Intelligence Aged Robotics
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Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support.

Journal of affective disorders Jan 11, 2025
BACKGROUND: Depression and cognitive impairments are prevalent among older adults, with evidence suggesting potential links to obesity and lipid metabolism disturbances. This study investigates the relationships between the triglyceride-glucose (TyG)...
Mendelian Randomization Analysis Male Triglycerides Middle Aged Humans Depression Blood Glucose Machine Learning Cognitive Dysfunction Nutrition Surveys Female Body Mass Index Aged Obesity
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Importance of neural network complexity for the automatic segmentation of individual thigh muscles in MRI images from patients with neuromuscular diseases.

Magma (New York, N.Y.) Jan 11, 2025
OBJECTIVE: Segmentation of individual thigh muscles in MRI images is essential for monitoring neuromuscular diseases and quantifying relevant biomarkers such as fat fraction (FF). Deep learning approaches such as U-Net have demonstrated effectiveness...
Humans Neural Networks, Computer Algorithms Adult Male Middle Aged Deep Learning Image Processing, Computer-Assisted Databases, Factual Female Reproducibility of Results Aged Image Interpretation, Computer-Assisted Neuromuscular Diseases Magnetic Resonance Imaging Muscle, Skeletal Adipose Tissue Thigh
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Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment.

Open heart Jan 11, 2025
BACKGROUND: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis im...
Algorithms Retrospective Studies Female Reproducibility of Results Coronary Vessels Humans Predictive Value of Tests Aged Computed Tomography Angiography Coronary Angiography Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Male Coronary Stenosis Middle Aged Coronary Artery Disease Severity of Illness Index Observer Variation
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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

Open heart Jan 11, 2025
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...
Male Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Retrospective Studies Female Reproducibility of Results Aged Computed Tomography Angiography Coronary Stenosis Humans
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Developing a decision support tool to predict delayed discharge from hospitals using machine learning.

BMC health services research Jan 11, 2025
BACKGROUND: The growing demand for healthcare services challenges patient flow management in health systems. Alternative Level of Care (ALC) patients who no longer need acute care yet face discharge barriers contribute to prolonged stays and hospital...
Adult Machine Learning Male Patient Discharge Decision Support Techniques Humans Middle Aged Nova Scotia Female Length of Stay Neural Networks, Computer Aged
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A prediction study on the occurrence risk of heart disease in older hypertensive patients based on machine learning.

BMC geriatrics Jan 11, 2025
OBJECTIVE: Constructing a predictive model for the occurrence of heart disease in elderly hypertensive individuals, aiming to provide early risk identification.
Follow-Up Studies Heart Diseases Risk Assessment Humans China Machine Learning Hypertension Risk Factors Female Longitudinal Studies Aged Male Middle Aged
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Identification of biomarkers for knee osteoarthritis through clinical data and machine learning models.

Scientific reports Jan 11, 2025
Knee osteoarthritis (KOA) represents a progressive degenerative disorder characterized by the gradual erosion of articular cartilage. This study aimed to develop and validate biomarker-based predictive models for KOA diagnosis using machine learning ...
Osteoarthritis, Knee Middle Aged ROC Curve Support Vector Machine Decision Trees Humans Machine Learning Biomarkers Female Aged Male
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