AIMC Topic: Age Factors
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Gated cardiac CT in infants: What can we expect from deep learning image reconstruction algorithm?
Journal of cardiovascular computed tomography
Mar 12, 2024
BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). Deep Learning Image Reconstruction (DLIR) could improve image quality while minimizing the radiation dose.
Phantoms, Imaging
Computed Tomography Angiography
Radiation Exposure
Cardiac-Gated Imaging Techniques
Infant
Predictive Value of Tests
Humans
Deep Learning
Coronary Angiography
Reproducibility of Results
Electrocardiography
Radiographic Image Interpretation, Computer-Assisted
Age Factors
Radiation Dosage
Heart Defects, Congenital
Improved Arterial Stiffness Indices 3 and 6 Months after Living-donor Renal Transplantation.
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
Mar 11, 2024
Arterial stiffness is a non-traditional risk factor of cardiovascular disease and may explain part of the excess cardiovascular risk in chronic kidney disease patients. Successful renal transplantation (RT) may restore renal function and improve seve...
Perspective analysis of assistive robots for elderly in India.
Disability and rehabilitation. Assistive technology
Mar 7, 2024
PURPOSE: Assistive technology for elderly are advancing, and this study aimed to analyse the Indian perspective on utilising assistive robot technology for aiding elderly individuals.
Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?
International journal of radiation oncology, biology, physics
Jan 19, 2024
PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adaptive radiation therapy and radiation therapy planning. However, their performance on pediatric compu...
Heterogeneous treatment effects of coronary artery bypass grafting in ischemic cardiomyopathy: A machine learning causal forest analysis.
The Journal of thoracic and cardiovascular surgery
Sep 15, 2023
OBJECTIVES: We aim to evaluate the heterogeneous treatment effects of coronary artery bypass grafting in patients with ischemic cardiomyopathy and to identify a group of patients to have greater benefits from coronary artery bypass grafting compared ...
Understanding the Impact of Aging on Attractiveness Using a Machine Learning Model of Facial Age Progression.
Facial plastic surgery & aesthetic medicine
Apr 12, 2023
Advances in machine learning age progression technology offer the unique opportunity to better understand the public's perception on the aging face. To compare how observers perceive attractiveness and traditional gender traits in faces created wit...
Age-specific biomechanical challenges and engagement in dynamic balance training with robotic or virtual real-time visual feedback.
Journal of biomechanics
Mar 31, 2023
Challenging balance training that targets age-related neuromuscular and motor coordination deficits is needed for effective fall prevention therapy. Goal-directed training can provide intrinsically motivating balance activities but may not equally ch...
Age-specific risk factors for the prediction of obesity using a machine learning approach.
Frontiers in public health
Jan 17, 2023
Machine Learning is a powerful tool to discover hidden information and relationships in various data-driven research fields. Obesity is an extremely complex topic, involving biological, physiological, psychological, and environmental factors. One suc...
An artificial-intelligence-based age-specific template construction framework for brain structural analysis using magnetic resonance images.
Human brain mapping
Oct 21, 2022
It is an essential task to construct brain templates and analyze their anatomical structures in neurological and cognitive science. Generally, templates constructed from magnetic resonance imaging (MRI) of a group of subjects can provide a standard r...
Classification of Electroencephalogram Signal for Developing Brain-Computer Interface Using Bioinspired Machine Learning Approach.
Computational intelligence and neuroscience
Feb 25, 2022
Transforming human intentions into patterns to direct the devices connected externally without any body movements is called Brain-Computer Interface (BCI). It is specially designed for rehabilitation patients to overcome their disabilities. Electroen...
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