Ophthalmology

Brief communication: Three errors and two problems in a recent paper: gazeNet: End-to-end eye-movement event detection with deep neural networks (Zemblys, Niehorster, and Holmqvist, 2019).

Zemblys et al. (Behavior Research Methods, 51(2), 840-864, 2019) reported on a method for the classification of eye-movements ("gazeNet"). I have found three errors and two problems with that paper that are explained herein. Error 1: The gazeNet classification method was built assuming that a hand-scored dataset from Lund University was all collected at 500 Hz, but in fact, six of the 34 recording...

Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence.

Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight and very preterm infants in the United States. With improved survival of smaller babies, more infants are at risk for ROP, yet there is an increasing shortage of providers to screen and treat ROP. Through a literature review of new and emerging technologies, screening criteria, and analysis of a na...

Re: Phene et al.: Deep learning and glaucoma specialists: the relative importance of optic disc features to predict glaucoma referral in fundus photographs (Ophthalmology. 2019;126:1627-1639).

Prior-Attention Residual Learning for More Discriminative COVID-19 Screening in CT Images.

We propose a conceptually simple framework for fast COVID-19 screening in 3D chest CT images. The framework can efficiently predict whether or not a C...

Wireless steerable vision for live insects and insect-scale robots.

Vision serves as an essential sensory input for insects but consumes substantial energy resources. The cost to support sensitive photoreceptors has le...

The potential application of artificial intelligence for diagnosis and management of glaucoma in adults.

BACKGROUND: Glaucoma is the most frequent cause of irreversible blindness worldwide. There is no cure, but early detection and treatment can slow the ...

Characterization of Drusen and Hyperreflective Foci as Biomarkers for Disease Progression in Age-Related Macular Degeneration Using Artificial Intelligence in Optical Coherence Tomography.

IMPORTANCE: The morphologic changes and their pathognomonic distribution in progressing age-related macular degeneration (AMD) are not well understood...

Artificial intelligence in cornea, refractive, and cataract surgery.

PURPOSE OF REVIEW: The subject of artificial intelligence has recently been responsible for the advancement of many industries including aspects of me...

Refractive Predictability Using the IOLMaster 700 and Artificial Intelligence-Based IOL Power Formulas Compared to Standard Formulas.

PURPOSE: To investigate the accuracy of intraocular lens (IOL) power calculation formulas using swept-source optical coherence tomography (SS-OCT).

Computational framework for fusing eye movements and spoken narratives for image annotation.

Despite many recent advances in the field of computer vision, there remains a disconnect between how computers process images and how humans understan...

Volumetric Choroidal Segmentation Using Sequential Deep Learning Approach in High Myopia Subjects.

Many ocular diseases are associated with choroidal changes. Therefore, it is crucial to be able to segment the choroid to study its properties. Previo...

A Multi-Label Deep Learning Model with Interpretable Grad-CAM for Diabetic Retinopathy Classification.

The characteristics of diabetic retinopathy (DR) fundus images generally consist of multiple types of lesions which provided strong evidence for the o...

A Comparison of Manual and Robot Assisted Retinal Vein Cannulation in Chicken Chorioallantoic Membrane.

Retinal vein occlusion (RVO) is a vision threatening condition occurring in the central or the branch retinal veins. Risk factors include but are not ...

A Preliminary Study of Predicting Effectiveness of Anti-VEGF Injection Using OCT Images Based on Deep Learning.

Deep learning based radiomics have made great progress such as CNN based diagnosis and U-Net based segmentation. However, the prediction of drug effec...

Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.

BACKGROUND: Deep learning (DL) has demonstrated human expert levels of performance for medical image classification in a wide array of medical fields,...

The retina revolution: signaling pathway therapies, genetic therapies, mitochondrial therapies, artificial intelligence.

PURPOSE OF REVIEW: The aim of this article is to review and discuss the history, current state, and future implications of promising biomedical offeri...

Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients w...

Artificial Intelligence for Refractive Surgery Screening: Finding the Balance Between Myopia and Hype-ropia.

[Multicenter comparison of complications after robot-assisted and open simple prostatectomy].

INTRODUCTION: Robot-assisted simple prostatectomy (RASP) is a relatively new minimally invasive procedure for surgical treatment to manage symptomatic...

Recent developments in pediatric retina.

PURPOSE OF REVIEW: Pediatric retina is an exciting, but also challenging field, where patient age and cooperation can limit ease of diagnosis of a bro...