Validity of Administrative Claims and Electronic Health Registry Data From a Single Practice for Eye Health Surveillance.

Importance: Diagnostic information from administrative claims and electronic health record (EHR) data may serve as an important resource for surveillance of vision and eye health, but the accuracy and validity of these sources are unknown.

Objective: To estimate the accuracy of diagnosis codes in administrative claims and EHRs compared to retrospective medical record review.

Design, Setting, And Participants: This cross-sectional study compared the presence and prevalence of eye disorders based on diagnostic codes in EHR and claims records vs clinical medical record review at University of Washington-affiliated ophthalmology or optometry clinics from May 2018 to April 2020.

Comparing Telephone Survey Responses to Best-Corrected Visual Acuity to Estimate the Accuracy of Identifying Vision Loss: Validation Study.

Background: Self-reported questions on blindness and vision problems are collected in many national surveys. Recently released surveillance estimates on the prevalence of vision loss used self-reported data to predict variation in the prevalence of objectively measured acuity loss among population groups for whom examination data are not available. However, the validity of self-reported measures to predict prevalence and disparities in visual acuity has not been established.

Flipped classroom approach to global outreach: cross-cultural teaching of horizontal strabismus to Chinese ophthalmology residents.

Aim: To evaluate the flipped classroom model for teaching horizontal strabismus didactics in an ophthalmology residency program in China as part of a visiting professorship from the United States.

Methods: Residents from an ophthalmology residency program in China were invited to participate in flipped classroom sessions taught by an experienced American ophthalmology faculty in 2018. Residents were instructed to watch a pre-class video lecture prior to the in-class-case-based activity.

Predictors of Long-term Ophthalmic Complications after Closed Globe Injuries Using the Intelligent Research in Sight (IRIS®) Registry.

Purpose: To identify clinical factors associated with the need for future surgical intervention following closed globe ocular trauma.

Design: Retrospective cohort study.

Subjects Participants And/or Controls: Patients in the American Academy of Ophthalmology Intelligent Research in Sight (IRIS®) Registry with a diagnosis of closed globe ocular trauma occurring between 2013 and 2019, identified using and Systematized Nomenclature of Medicine codes.

Detection of Nonexudative Macular Neovascularization on Structural OCT Images Using Vision Transformers.

Purpose: A deep learning model was developed to detect nonexudative macular neovascularization (neMNV) using OCT B-scans.

Design: Retrospective review of a prospective, observational study.

Participants: Normal control eyes and patients with age-related macular degeneration (AMD) with and without neMNV.

Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations.

Purpose: To create an unsupervised cross-domain segmentation algorithm for segmenting intraretinal fluid and retinal layers on normal and pathologic macular OCT images from different manufacturers and camera devices.

Design: We sought to use generative adversarial networks (GANs) to generalize a segmentation model trained on one OCT device to segment B-scans obtained from a different OCT device manufacturer in a fully unsupervised approach without labeled data from the latter manufacturer.

Participants: A total of 732 OCT B-scans from 4 different OCT devices (Heidelberg Spectralis, Topcon 1000, Maestro2, and Zeiss Plex Elite 9000).

Visual Field Endpoints for Neuroprotective Trials: A Case for AI-Driven Patient Enrichment.

Purpose: To evaluate whether an artificial intelligence (AI) model can better select candidates that would demonstrate visual field (VF) progression, in order to shorten the duration or the number of patients needed for a clinical trial.

Design: Retrospective cohort study.

Methods: 7428 eyes of 3871 patients from the University of Washington Department of Ophthalmology VF Dataset were included.

UWHVF: A Real-World, Open Source Dataset of Perimetry Tests From the Humphrey Field Analyzer at the University of Washington.

Purpose: This article describes the Humphrey field analyzer (HFA) dataset from the Department of Ophthalmology at the University of Washington.

Methods: Pointwise sensitivities were extracted from HFA 24-2, stimulus III visual fields (VF). Total deviation (TD), mean TD (MTD), pattern deviation, and pattern standard deviation (PSD) were calculated.

The flipped-classroom approach to teaching horizontal strabismus in ophthalmology residency: a multicentered randomized controlled study.

Background: The flipped-classroom involves watching prerecorded lectures at home followed by group learning exercises within the classroom. This study compares the flipped classroom approach with the traditional classroom for teaching horizontal strabismus didactics in ophthalmology residency.

Methods: In this multicenter, randomized controlled survey study from October 2017 to July 2018, 110 ophthalmology residents were taught esotropia and exotropia sequentially, randomized by order and classroom style.

PeriorbitAI: Artificial Intelligence Automation of Eyelid and Periorbital Measurements.

Purpose: To develop a deep learning semantic segmentation network to automate the assessment of 8 periorbital measurements DESIGN: Development and validation of an artificial intelligence (AI) segmentation algorithm METHODS: A total of 418 photographs of periorbital areas were used to train a deep learning semantic segmentation model to segment iris, aperture, and brow areas. These data were used to develop a post-processing algorithm that measured margin reflex distance (MRD) 1 and 2, medial canthal height (MCH), lateral canthal height (LCH), medial brow height (MBH), lateral brow height (LBH), medial intercanthal distance (MID), and lateral intercanthal distance (LID). The algorithm validity was evaluated on a prospective hold-out test set against 3 graders.