Retinal imaging in Alzheimer s disease - Journal of Neurology . . . ABSTRACT Identifying biomarkers of Alzheimer’s disease (AD) will accelerate the understanding of its pathophysiology, facilitate screening and risk stratification, and aid in developing new therapies Developments in non- invasive retinal imaging technologies, including optical coherence tomography (OCT), OCT angiography and digital retinal photography, have provided a means to study
A deep learning model for detection of Alzheimers disease . . . - PubMed Our main aim was to develop a bilateral model to detect Alzheimer's disease-dementia from retinal photographs alone We designed and internally validated the bilateral deep learning model using retinal photographs from six studies We used the EfficientNet-b2 network as the backbone of the model to extract features from the images
Carol YL CHEUNG – 中大眼科 CUHK DOVS Prof Cheung developed the world′s first deep-learning model using fundus photographs alone to detect Alzheimer′s disease Prof Cheung developed a deep-learning system for the assessment of cardiovascular disease risk via the measurement of retinal-vessel calibre
Artificial intelligence for detection of Alzheimers disease . . . In The Lancet Digital Health, Carol Y Cheung and colleagues1 describe a deep learning model for the detection of Alzheimer's disease from retinal photographs The authors trained a supervised deep learning algorithm using six retrospective datasets from Singapore, Hong Kong and the UK In the training of the model, 526 people with Alzheimer's disease and 2999 without the disease were enrolled
Retinal neuronal and vascular imaging measures are significantly . . . Alzheimer's Disease (AD) is associated with pathological changes in the brain that result from neurodegeneration and vascular disease processes Early diagnosis and early intervention for AD are considered important mechanisms to delay progression of disease for managing the worldwide impact of dementia Difficult to identify early AD
Value proposition of retinal imaging in Alzheimers disease screening . . . Alzheimer's disease (AD) is the leading cause of dementia worldwide Current diagnostic modalities of AD generally focus on detecting the presence of amyloid β and tau protein in the brain (for example, positron emission tomography [PET] and cerebrospinal fluid testing), but these are limited by their high cost, invasiveness, and lack of expertise Retinal imaging exhibits potential in AD
Dr Carol YL CHEUNG’s team develops the world’s first AI model using . . . Dr Carol YL CHEUNG, Associate Professor in the Department of Ophthalmology and Visual Sciences at The Chinese University of Hong Kong (CUHK)′s Faculty of Medicine (CU Medicine) has led an international team to successfully develop the world′s first artificial intelligence (AI) model that can detect Alzheimer′s disease solely through fundus photographs or images of the retina The model
Deep Reinforcement Learning-Based Retinal Imaging in Alzheimers . . . Alzheimer's disease (AD) remains a global health challenge in the 21st century due to its increasing prevalence as the major cause of dementia State-of-the-art artificial intelligence (AI)-based tests could potentially improve population-based strategies to detect and manage AD Current retinal ima …
Deep Reinforcement Learning-Based Retinal Imaging in Alzheimer’s . . . Alzheimer’s disease (AD) remains a global health challenge in the 21st century due to its increasing prevalence as the major cause of dementia State-of-the-art artificial intelligence (AI)-based tests could potentially improve population-based strategies to detect and manage AD Current retinal imaging demonstrates immense potential as a non-invasive screening measure for AD, by studying