AIMC Topic: UK Biobank

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Uncovering Predictors of Low Hippocampal Volume: Evidence from a Large-Scale Machine-Learning-Based Study in the UK Biobank.

Neuroepidemiology
INTRODUCTION: Hippocampal atrophy is an established biomarker for conversion from the normal ageing process to developing cognitive impairment and dementia. This study used a novel hypothesis-free machine-learning approach, to uncover potential risk ...

Association between deep learning measured retinal vessel calibre and incident myocardial infarction in a retrospective cohort from the UK Biobank.

BMJ open
BACKGROUND: Cardiovascular disease is a leading cause of global death. Prospective population-based studies have found that changes in retinal microvasculature are associated with the development of coronary artery disease. Recently, artificial intel...

Deep learning predicts prevalent and incident Parkinson's disease from UK Biobank fundus imaging.

Scientific reports
Parkinson's disease is the world's fastest-growing neurological disorder. Research to elucidate the mechanisms of Parkinson's disease and automate diagnostics would greatly improve the treatment of patients with Parkinson's disease. Current diagnosti...

Deep neural network-estimated age using optical coherence tomography predicts mortality.

GeroScience
The concept of biological age has emerged as a measurement that reflects physiological and functional decline with ageing. Here we aimed to develop a deep neural network (DNN) model that predicts biological age from optical coherence tomography (OCT)...

Nonlinear Associations of Accelerometer-Based Sedentary Time With Cognitive Functions in the UK Biobank.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Device-based sedentary time shows a nonlinear association with incident dementia among older adults. However, associations between sedentary time and cognitive performance have been inconsistent. We examined potential nonlinear associatio...

Brain Aging in Patients With Cardiovascular Disease From the UK Biobank.

Human brain mapping
The brain undergoes complex but normal structural changes during the aging process in healthy adults, whereas deviations from the normal aging patterns of the brain can be indicative of various conditions as well as an increased risk for the developm...

Processing UK Biobank High Resolution Accelerometry Data for Unsupervised Identification of Activity Profiles and Their Differences in Clinically Relevant Outcome Parameters - The ATLAS Index Revisited.

Studies in health technology and informatics
Accelerometer data obtained with wearable devices over extended periods of time provides objective, valuable information on activity behavior. Building on previous work to derive easy-to-interpret activity parameters - the Activity Types from Long-te...

Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach.

European journal of preventive cardiology
AIMS: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors using linear multivariate models. This study explores the potential of integrating positive psychosocial factors (PPFs), including happines...

Evaluation of deep learning estimation of whole heart anatomy from automated cardiovascular magnetic resonance short- and long-axis analyses in UK Biobank.

European heart journal. Cardiovascular Imaging
AIMS: Standard methods of heart chamber volume estimation in cardiovascular magnetic resonance (CMR) typically utilize simple geometric formulae based on a limited number of slices. We aimed to evaluate whether an automated deep learning neural netwo...

Fracture risk prediction in postmenopausal women with traditional and machine learning models in a nationwide, prospective cohort study in Switzerland with validation in the UK Biobank.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Fracture prediction is essential in managing patients with osteoporosis and is an integral component of many fracture prevention guidelines. We aimed to identify the most relevant clinical fracture risk factors in contemporary populations by training...