AIMC Topic:
Middle Aged

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A deep learning approach versus expert clinician panel in the classification of posterior circulation infarction.

NeuroImage. Clinical Jan 12, 2025
BACKGROUND: Posterior circulation infarction (POCI) is common. Imaging techniques such as non-contrast-CT (NCCT) and diffusion-weighted-magnetic-resonance-imaging commonly fail to detect hyperacute POCI. Studies suggest expert inspection of Computed ...
Registries Aged, 80 and over Humans Male Tomography, X-Ray Computed Middle Aged Female Deep Learning Aged
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Clinical validation of artificial intelligence-based single-subject morphometry without normative reference database.

Journal of Alzheimer's disease : JAD Jan 12, 2025
BACKGROUND: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative...
Humans Alzheimer Disease Neural Networks, Computer Positron-Emission Tomography Artificial Intelligence Atrophy Databases, Factual Aged, 80 and over Brain Male Female Middle Aged Aged Magnetic Resonance Imaging Neurodegenerative Diseases
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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...
Tuberculosis, Spinal Generative Artificial Intelligence Magnetic Resonance Imaging Diagnosis, Differential Spinal Neoplasms Algorithms Retrospective Studies Female Humans Aged Machine Learning Young Adult Adult Sensitivity and Specificity Male Middle Aged
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Assessing ChatGPT's accuracy and reliability in asthma general knowledge: implications for artificial intelligence use in public health education.

The Journal of asthma : official journal of the Association for the Care of Asthma Jan 11, 2025
BACKGROUND: Integrating Artificial Intelligence (AI) into public health education represents a pivotal advancement in medical knowledge dissemination, particularly for chronic diseases such as asthma. This study assesses the accuracy and comprehensiv...
Humans Artificial Intelligence Female Public Health Adult Reproducibility of Results Surveys and Questionnaires Asthma Generative Artificial Intelligence Male Health Knowledge, Attitudes, Practice Middle Aged Health Education
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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...
Humans Brain Retrospective Studies Female Aged Dementia Male Imaging, Three-Dimensional Middle Aged Magnetic Resonance Imaging Deep Learning Cognitive Dysfunction
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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 Humans Machine Learning Triglycerides Blood Glucose Aged Female Nutrition Surveys Male Body Mass Index Middle Aged Obesity Depression Cognitive Dysfunction
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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...
Middle Aged Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Muscle, Skeletal Female Adipose Tissue Humans Reproducibility of Results Thigh Neural Networks, Computer Aged Image Interpretation, Computer-Assisted Algorithms Adult Databases, Factual Neuromuscular Diseases Male
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Deep Neural Network Analysis of the 12-Lead Electrocardiogram Distinguishes Patients With Congenital Long QT Syndrome From Patients With Acquired QT Prolongation.

Mayo Clinic proceedings Jan 11, 2025
OBJECTIVE: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysis of the 12-lead electrocardiogram (ECG) can distinguish patients with long QT syndrome (LQTS) from those with acquired QT prolongation.
Adult Sensitivity and Specificity Male Middle Aged Adolescent Humans Neural Networks, Computer Female Young Adult Child Electrocardiography Diagnosis, Differential Long QT Syndrome
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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...
Aged Male Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Observer Variation Artificial Intelligence Algorithms Retrospective Studies Female Reproducibility of Results Coronary Vessels Humans Computed Tomography Angiography Coronary Stenosis
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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 ...
Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Retrospective Studies Coronary Angiography Humans Female Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Coronary Vessels Aged Computed Tomography Angiography Male Coronary Stenosis
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