AIMC Topic: Aged, 80 and over

Clear Filters Showing 3181 to 3190 of 3658 articles

Deep Learning Technique for Automatic Segmentation of Proximal Hip Musculoskeletal Tissues From CT Scan Images: A MrOS Study.

Journal of cachexia, sarcopenia and muscle
BACKGROUND: Age-related conditions, such as osteoporosis and sarcopenia, alongside chronic diseases, can result in significant musculoskeletal tissue loss. This impacts individuals' quality of life and increases risk of falls and fractures. Computed ...

Real world clinical experience of using Brainomix e-CTA software in a medium size acute National Health Service Trust.

The British journal of radiology
OBJECTIVES: Artificial intelligence (AI) software including Brainomix "e-CTA" which detect large vessel occlusions (LVO) have clinical potential. We hypothesized that in real world use where prevalence is low, its clinical utility may be overstated.

Predicting Postoperative Circulatory Complications in Older Patients: A Machine Learning Approach.

Biomedical and environmental sciences : BES
OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients.

Accuracy of artificial intelligence-based simulation for assessing lung vessels and volume using unenhanced computed tomography.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The advantages of preoperative three-dimensional (3D) image simulations, which require enhanced computed tomography (ECT), for anatomical lung resection are well documented. However, the necessity for contrast agent presents a significant...

Structure-Function Correlation of Deep-Learning Quantified Ellipsoid Zone and Retinal Pigment Epithelium Loss and Microperimetry in Geographic Atrophy.

Investigative ophthalmology & visual science
PURPOSE: The purpose of this study was to define structure-function correlation of geographic atrophy (GA) on optical coherence tomography (OCT) and functional testing on microperimetry (MP) based on deep-learning (DL)-quantified spectral-domain OCT ...

Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease.

European heart journal
BACKGROUND AND AIMS: Robust and convenient risk stratification of patients with paediatric and adult congenital heart disease (CHD) is lacking. This study aims to address this gap with an artificial intelligence-enhanced electrocardiogram (ECG) tool ...

Predicting amyloid beta accumulation in cognitively unimpaired older adults: Cognitive assessments provide no additional utility beyond demographic and genetic factors.

Alzheimer's & dementia : the journal of the Alzheimer's Association
BACKGROUND: Integrating non-invasive measures to estimate abnormal amyloid beta accumulation (Aβ+) is key to developing a screening tool for preclinical Alzheimer's disease (AD). The predictive capability of standard neuropsychological tests in estim...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.

Developing and validating a prediction tool for cerebral amyloid angiopathy neuropathological severity.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Cerebral amyloid angiopathy (CAA) is a cerebrovascular condition, the severity of which can only be determined post mortem. Here, we developed machine learning models, the Florey CAA Score (FCAAS), to predict CAA severity (none/mild/mod...