Ophthalmology

ACCV: automatic classification algorithm of cataract video based on deep learning.

PURPOSE: A real-time automatic cataract-grading algorithm based on cataract video is proposed.

Detection of Diabetic Eye Disease from Retinal Images Using a Deep Learning Based CenterNet Model.

Diabetic retinopathy (DR) is an eye disease that alters the blood vessels of a person suffering from diabetes. Diabetic macular edema (DME) occurs when DR affects the macula, which causes fluid accumulation in the macula. Efficient screening systems require experts to manually analyze images to recognize diseases. However, due to the challenging nature of the screening method and lack of trained h...

DeepUWF: An Automated Ultra-Wide-Field Fundus Screening System via Deep Learning.

The emerging ultra-wide field of view (UWF) fundus color imaging is a powerful tool for fundus screening. However, manual screening is labor-intensive...

Development and validation of a deep learning system to classify aetiology and predict anatomical outcomes of macular hole.

AIMS: To develop a deep learning (DL) model for automatic classification of macular hole (MH) aetiology (idiopathic or secondary), and a multimodal de...

Real-world artificial intelligence-based opportunistic screening for diabetic retinopathy in endocrinology and indigenous healthcare settings in Australia.

This study investigated the diagnostic performance, feasibility, and end-user experiences of an artificial intelligence (AI)-assisted diabetic retinop...

Automated detection of retinal exudates and drusen in ultra-widefield fundus images based on deep learning.

BACKGROUND: Retinal exudates and/or drusen (RED) can be signs of many fundus diseases that can lead to irreversible vision loss. Early detection and t...

Mathematical and computational modeling for the determination of optical parameters of breast cancer cell.

This study enumerates the quantitative measurement of optical parameters used in several diagnostic procedures for malignant tissue. Optical diagnosis...

Robot-assisted Exploration of Somatic Nerves in the Pelvis and Transection of the Sacrospinous Ligament for Alcock Canal Syndrome.

STUDY OBJECTIVE: Some articles have reported the surgical management of Alcock canal syndrome (ACS) using the transperineal [1], transgluteal [2], or ...

A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

OBJECTIVE: Diabetic macular edema (DME) is the primary cause of vision loss among individuals with diabetes mellitus (DM). We developed, validated, an...

Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.

An efficient automatic decision support system for detection of retinal disorders is important and is the need of the hour. Optical Coherence Tomograp...

Understanding terror states of online users in the context of COVID-19: An application of Terror Management Theory.

The COVID-19 pandemic has provided psych challenges for many in society. One such challenge is the anxiety that is created in many people faced with t...

Machine learning in optical coherence tomography angiography.

Optical coherence tomography angiography (OCTA) offers a noninvasive label-free solution for imaging retinal vasculatures at the capillary level resol...

A deep learning algorithm for sleep stage scoring in mice based on a multimodal network with fine-tuning technique.

Sleep stage scoring is important to determine sleep structure in preclinical and clinical research. The aim of this study was to develop an automatic ...

MEGnet: Automatic ICA-based artifact removal for MEG using spatiotemporal convolutional neural networks.

Magnetoencephalography (MEG) is a functional neuroimaging tool that records the magnetic fields induced by neuronal activity; however, signal from non...

Emergence of non-artificial intelligence digital health innovations in ophthalmology: A systematic review.

The prominent rise of digital health in ophthalmology is evident in the current age of Industry 4.0. Despite the many facets of digital health, there ...

Deep learning-assisted (automatic) diagnosis of glaucoma using a smartphone.

BACKGROUND/AIMS: To validate a deep learning algorithm to diagnose glaucoma from fundus photography obtained with a smartphone.

Using Big Data-Based Neural Network Parallel Optimization Algorithm in Sports Fatigue Warning.

In high-paced and efficient life and work, fatigue is one of the important factors that cause accidents such as traffic and medical accidents. This st...

Economic Evaluations of Artificial Intelligence in Ophthalmology.

Artificial intelligence (AI) is expected to cause significant medical quality enhancements and cost-saving improvements in ophthalmology. Although the...

Ocular blood flow as it relates to race and disease on glaucoma.

Glaucoma is a multifactorial progressive and degenerative optic neuropathy representing one of the world's leading cause of irreversible blindness. Cu...

Using deep learning to identify the recurrent laryngeal nerve during thyroidectomy.

Surgeons must visually distinguish soft-tissues, such as nerves, from surrounding anatomy to prevent complications and optimize patient outcomes. An a...