Background To examine whether the clinical performance of predicting late age‐related
macular degeneration (AMD) development is improved through using multimodal imaging …

The target of dynamic prediction is to provide individualized risk predictions over time which
can be updated as new data become available. Motivated by establishing a dynamic …

Contrastive pretraining provides robust representations by ensuring their invariance to
different image transformations while simultaneously preventing representational collapse …

Diabetic retinopathy (DR) is one of the most common retinal vascular diseases and one of
the main causes of blindness worldwide. Early detection and treatment can effectively delay …

Early detection of high-risk individuals is crucial for healthcare systems to cope with
changing demographics and an ever-increasing patient population. Images of the retinal …

Recent developments in Computer-aided Diagnosis (CAD) systems as a countermeasure to
the increasing number of untreated cases of eye diseases related to visual impairment (such …

Age-related macular degeneration (AMD) is a leading cause of blindness in the developed
world. In this study, we compare the performance of retinal fundus images and genetic …

Age-related macular degeneration (AMD) affects∼ 8.7% of the world's population and is
projected to affect 288 million individuals by the year 2040. 1 The availability of anti …

Artificial intelligence for diagnosing exudative age‐related macular degeneration - PMC Back
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Objective: To combine medical knowledge and medical data to interpretably predict the risk
of disease. Methods: We formulated the disease prediction task as a random walk along a …