AIMC Topic: Aged

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Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation.

NeuroImage
White matter fiber clustering is an important strategy for white matter parcellation, which enables quantitative analysis of brain connections in health and disease. In combination with expert neuroanatomical labeling, data-driven white matter fiber ...

Associations Between Older Adults' Loneliness and Acceptance of Socially Assistive Robots: A Cross-Sectional Study.

Journal of gerontological nursing
The use of socially assistive robots (SARs) to enable older adults (aged ≥65 years) to live independently for as long as possible has been researched for several years. Of particular interest is the way SARs can combat loneliness. A quantitative cros...

Clinically explainable machine learning models for early identification of patients at risk of hospital-acquired urinary tract infection.

The Journal of hospital infection
BACKGROUND: Machine learning (ML) models for early identification of patients at risk of hospital-acquired urinary tract infection (HA-UTI) may enable timely and targeted preventive and therapeutic strategies. However, clinicians are often challenged...

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...

Comparison of Machine Learning Models for Brain Age Prediction Using Six Imaging Modalities on Middle-Aged and Older Adults.

Sensors (Basel, Switzerland)
Machine learning (ML) has transformed neuroimaging research by enabling accurate predictions and feature extraction from large datasets. In this study, we investigate the application of six ML algorithms (Lasso, relevance vector regression, support v...

Identifying Reasons for Statin Nonuse in Patients With Diabetes Using Deep Learning of Electronic Health Records.

Journal of the American Heart Association
Background Statins are guideline-recommended medications that reduce cardiovascular events in patients with diabetes. Yet, statin use is concerningly low in this high-risk population. Identifying reasons for statin nonuse, which are typically describ...

Incidental findings on CT scans for robot-assisted total joint arthroplasty.

ANZ journal of surgery
INTRODUCTION: This study documented the incidence of incidental findings from preoperative computerized-tomography (CT) scans obtained for robotic-arm-assisted total joint arthroplasty (TJA) and its effect on patient management.

Natural language processing techniques for studying language in pathological ageing: A scoping review.

International journal of language & communication disorders
BACKGROUND: In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowin...

Fully Automated Artificial Intelligence Assessment of Aortic Stenosis by Echocardiography.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Aortic stenosis (AS) is a common form of valvular heart disease, present in over 12% of the population age 75 years and above. Transthoracic echocardiography (TTE) is the first line of imaging in the adjudication of AS severity but is tim...