Ophthalmology

Multidimensional Tactile Sensor with a Thin Compound Eye-Inspired Imaging System.

Artificial tactile sensing for robots is a counterpart to the human sense of touch, serving as a feedback interface for sensing and interacting with the environment. A vision-based tactile sensor has emerged as a novel and advantageous branch of artificial tactile sensors. Compared with conventional tactile sensors, vision-based tactile sensors possess stronger potential thanks to acquiring multim...

Re: Christopher et al.: Deep learning approaches predict glaucomatous visual field damage from OCT optic nerve head en face images and retinal nerve fiber layer thickness maps (Ophthalmology. 2020;127:346-356).

KerNet: A Novel Deep Learning Approach for Keratoconus and Sub-Clinical Keratoconus Detection Based on Raw Data of the Pentacam HR System.

Keratoconus is one of the most severe corneal diseases, which is difficult to detect at the early stage (i.e., sub-clinical keratoconus) and possibly ...

Deep learning for predicting uncorrected refractive error using posterior segment optical coherence tomography images.

BACKGROUND/OBJECTIVES: This study aimed to evaluate a deep learning model for estimating uncorrected refractive error using posterior segment optical ...

Predicting crop root concentration factors of organic contaminants with machine learning models.

Accurate prediction of uptake and accumulation of organic contaminants by crops from soils is essential to assessing human exposure via the food chain...

Artificial intelligence for microbial biotechnology: beyond the hype.

It has been a landmark year for artificial intelligence (AI) and biotechnology. Perhaps the most noteworthy of these advances was Google DeepMind's Al...

Artificial intelligence applications and cataract management: A systematic review.

Artificial intelligence (AI)-based applications exhibit the potential to improve the quality and efficiency of patient care in different fields, inclu...

Refractive outcomes of second-eye adjustment methods on intraocular lens power calculation in second eye.

BACKGROUND: To investigate the refractive outcomes of second-eye adjustment (SEA) methods in different intraocular lens (IOL) power calculation formul...

Data-driven electrophysiological feature based on deep learning to detect epileptic seizures.

. To identify a new electrophysiological feature characterising the epileptic seizures, which is commonly observed in different types of epilepsy.. We...

Artificial intelligence-based detection of epimacular membrane from color fundus photographs.

Epiretinal membrane (ERM) is a common ophthalmological disorder of high prevalence. Its symptoms include metamorphopsia, blurred vision, and decreased...

State of the Art in Robot-Assisted Eye Surgery.

Despite the advantages that robot-assisted surgery can offer to patient care, its use in ophthalmic surgery has not yet progressed to the extent seen ...

Identification of Sex and Age from Macular Optical Coherence Tomography and Feature Analysis Using Deep Learning.

PURPOSE: To develop deep learning models for identification of sex and age from macular optical coherence tomography (OCT) and to analyze the features...

Deep learning versus ophthalmologists for screening for glaucoma on fundus examination: A systematic review and meta-analysis.

BACKGROUND: In this systematic review and meta-analysis, we aimed to compare deep learning versus ophthalmologists in glaucoma diagnosis on fundus exa...

Towards Scale and Position Invariant Task Classification using Normalised Visual Scanpaths in Clinical Fetal Ultrasound.

We present a method for classifying tasks in fetal ultrasound scans using the eye-tracking data of sonographers. The visual attention of a sonographer...

Accuracy of Using Generative Adversarial Networks for Glaucoma Detection: Systematic Review and Bibliometric Analysis.

BACKGROUND: Glaucoma leads to irreversible blindness. Globally, it is the second most common retinal disease that leads to blindness, slightly less co...

The Importance of Close Follow-Up in Patients with Early-Grade Diabetic Retinopathy: A Taiwan Population-Based Study Grading via Deep Learning Model.

(1) Background: Diabetic retinopathy (DR) can cause blindness. Current guidelines on diabetic eye care recommend more frequent eye examinations for mo...

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning.

Particle agglutination assays are widely adopted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic part...

The impact of training sample size on deep learning-based organ auto-segmentation for head-and-neck patients.

To investigate the impact of training sample size on the performance of deep learning-based organ auto-segmentation for head-and-neck cancer patients,...

Vision-Based Intelligent Perceiving and Planning System of a 7-DoF Collaborative Robot.

In this paper, an intelligent perceiving and planning system based on deep learning is proposed for a collaborative robot consisting of a 7-DoF (7-deg...

Clinically relevant deep learning for detection and quantification of geographic atrophy from optical coherence tomography: a model development and external validation study.

BACKGROUND: Geographic atrophy is a major vision-threatening manifestation of age-related macular degeneration, one of the leading causes of blindness...