AIMC Topic: Age Factors

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Assessing the Influence of B-US, CDFI, SE, and Patient Age on Predicting Molecular Subtypes in Breast Lesions Using Deep Learning Algorithms.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Our study aims to investigate the impact of B-mode ultrasound (B-US) imaging, color Doppler flow imaging (CDFI), strain elastography (SE), and patient age on the prediction of molecular subtypes in breast lesions.

Identifying low acuity Emergency Department visits with a machine learning approach: The low acuity visit algorithms (LAVA).

Health services research
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.

Correlating Age and Hematoma Volume with Extent of Midline Shift in Acute Subdural Hematoma Patients: Validation of an Artificial Intelligence Tool for Volumetric Analysis.

World neurosurgery
OBJECTIVE: Decision for intervention in acute subdural hematoma patients is based on a combination of clinical and radiographic factors. Age has been suggested as a factor to be strongly considered when interpreting midline shift (MLS) and hematoma v...

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
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
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
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
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
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
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...