Diabetic Macular Edema Detection Using End-to-End Deep Fusion Model and Anatomical Landmark Visualization on an Edge Computing Device.

Purpose: Diabetic macular edema (DME) is a common cause of vision impairment and blindness in patients with diabetes. However, vision loss can be prevented by regular eye examinations during primary care. This study aimed to design an artificial intelligence (AI) system to facilitate ophthalmology referrals by physicians.

Deep Learning for Automated Diabetic Retinopathy Screening Fused With Heterogeneous Data From EHRs Can Lead to Earlier Referral Decisions.

Purpose: Fundus images are typically used as the sole training input for automated diabetic retinopathy (DR) classification. In this study, we considered several well-known DR risk factors and attempted to improve the accuracy of DR screening.

Metphods: Fusing nonimage data (e.

Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy.

Purpose: To improve disease severity classification from fundus images using a hybrid architecture with symptom awareness for diabetic retinopathy (DR).

Methods: We used 26,699 fundus images of 17,834 diabetic patients from three Taiwanese hospitals collected in 2007 to 2018 for DR severity classification. Thirty-seven ophthalmologists verified the images using lesion annotation and severity classification as the ground truth.

Assessing the consistency of the treatment effect under the discrete random effects model in multiregional clinical trials.

In recent years, developing pharmaceutical products via multiregional clinical trials (MRCTs) has become standard. Traditionally, an MRCT would assume that a treatment effect is uniform across regions. However, heterogeneity among regions may have impact upon the evaluation of a medicine's effect.

Weighted evidence approach of bridging study.

The ICH E5 Guidance facilitates the registration of medicine among ICH regions by recommending a framework for evaluating the impact of ethnic factors upon a medicine's effect. It further describes the use of bridging studies, when necessary, to allow extrapolation of foreign clinical data to a new region. Bridging studies are performed in a new region for medicines already approved in the original region.