Figure 1. Example case with diabetic macular edema. Source: George Magrath, MD Our work to date includes the creation of a DL algorithm to predict the presence of diabetic macular edema based on a ...

However, using artificial intelligence (AI) and deep learning (DL) algorithms ... and deep learning-based algorithms to diagnose eye-related disorders and diseases. A flowchart depicting the ...

In this video from the MVAPICH User Group, Abhinav Vishnu from PNNL presents: Scaling Deep Learning Algorithms on Extreme Scale Architectures. “Deep Learning (DL) is ubiquitous. Yet leveraging ...

Using these images may also allow for overcoming certain barriers with current DL algorithms. “Many cancer detection systems use deep learning (DL) algorithms for skin lesion diagnosis by ...

Deep learning (DL) algorithms use sophisticated neural networks, which mimic the human brain, to extract meaningful information from unstructured data, including text, audio and images.

DL algorithms are often computationally expensive, power-hungry, and require large memory to process complex and iterative operations of millions of parameters. Hence, training and inference of DL ...

A deep learning (DL) algorithm was trained, validated and tested on the fundus stereophotographs of participants enrolled in the Ocular Hypertension Treatment Study (OHTS), a randomized clinical ...