Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.

On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in the diagnosis and treatment of various ophthalmic conditions. In a session entitled Artificial Intelligence for Glaucoma, a panel of glaucoma specialists, researchers, industry experts, and patients convened to share current research on the application of AI to commonly used diagnostic modalities, including fundus photography, OCT imaging, standard automated perimetry, and gonioscopy. The conference participants focused on the use of AI as a tool for disease prediction, highlighted its ability to address inequalities, and presented the limitations of and challenges to its clinical application. The panelists discussion addressed AI and health equities from clinical, societal, and regulatory perspectives

Transition Zones between Healthy and Diseased Retina in Choroideremia (CHM) and Stargardt Disease (STGD) as Compared to Retinitis Pigmentosa (RP)

The transition zone between healthy and severely affected regions of the retina differ in structural abnormalities in patients with choroideremia, Stargardt disease, or retinitis pigmentosa

The Inner Segment/Outer Segment Border Seen on Optical Coherence Tomography Is Less Intense in Patients with Diminished Cone Function

The so-called IS/OS border visible on OCT scans is now thought to be the ellipsoids of the inner segment. This band of increased reflectivity is visible, but less intense, in patients with markedly reduced cone function secondary to achromatopsia and cone dystrophy