Ophthalmology

On Connections Between Regularizations for Improving DNN Robustness.

This paper analyzes regularization terms proposed recently for improving the adversarial robustness of deep neural networks (DNNs), from a theoretical point of view. Specifically, we study possible connections between several effective methods, including input-gradient regularization, Jacobian regularization, curvature regularization, and a cross-Lipschitz functional. We investigate them on DNNs w...

Prediction of corneal back surface power - Deep learning algorithm versus multivariate regression.

BACKGROUND: The corneal back surface is known to add some against the rule astigmatism, with implications in cataract surgery with toric lens implantation. This study aimed to set up and validate a deep learning algorithm to predict corneal back surface power from the corneal front surface power and biometric measures.

Machine Learning for Health: Algorithm Auditing & Quality Control.

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the rea...

Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.

IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; how...

Robot-assisted stereoelectroencephalography in young children: technical challenges and considerations.

Robot-assisted stereoelectroencephalography (sEEG) is frequently employed to localize epileptogenic zones in patients with medically refractory epilep...

A systematic review of sutureless vascular anastomosis technologies.

Vascular anastomoses typically involve a handsewn technique requiring significant surgical training, expertise, and time. The aim of our systematic re...

Role of Deep Learning in Predicting Aging-Related Diseases: A Scoping Review.

Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highl...

Image Quality Evaluation of Sanda Sports Video Based on BP Neural Network Perception.

In the special sports camera, there are subframes. A lens is composed of multiple frames. It will be unclear if a frame is cut out. The definition of ...

Development of deep learning-based detecting systems for pathologic myopia using retinal fundus images.

Globally, cases of myopia have reached epidemic levels. High myopia and pathological myopia (PM) are the leading cause of visual impairment and blindn...

Adaptive Control Improves Sclera Force Safety in Robot-Assisted Eye Surgery: A Clinical Study.

The integration of robotics into retinal microsurgery leads to a reduction in surgeon perception of tool-to-tissue interaction forces. This blunting o...

An Automatic Detection and Classification System of Five Stages for Hypertensive Retinopathy Using Semantic and Instance Segmentation in DenseNet Architecture.

The stage and duration of hypertension are connected to the occurrence of Hypertensive Retinopathy (HR) of eye disease. Currently, a few computerized ...

Evaluation Technology of Classroom Students' Learning State Based on Deep Learning.

Facial features are an effective representation of students' fatigue state, and the eye is more closely related to fatigue state. However, there are t...

Optically Modulated HfS-Based Synapses for Artificial Vision Systems.

The simulation of human brain neurons by synaptic devices could be an effective strategy to break through the notorious "von Neumann Bottleneck" and "...

Deep learning for bone marrow cell detection and classification on whole-slide images.

Bone marrow (BM) examination is an essential step in both diagnosing and managing numerous hematologic disorders. BM nucleated differential count (NDC...

Non-transfer Deep Learning of Optical Coherence Tomography for Post-hoc Explanation of Macular Disease Classification.

Deep transfer learning is a popular choice for classifying monochromatic medical images using models that are pretrained by natural images with color ...

EEGdenoiseNet: a benchmark dataset for deep learning solutions of EEG denoising.

Deep learning (DL) networks are increasingly attracting attention across various fields, including electroencephalography (EEG) signal processing. The...

Deep learning on fundus images detects glaucoma beyond the optic disc.

Although unprecedented sensitivity and specificity values are reported, recent glaucoma detection deep learning models lack in decision transparency. ...

Prediction of postoperative visual acuity after vitrectomy for macular hole using deep learning-based artificial intelligence.

PURPOSE: To create a model for prediction of postoperative visual acuity (VA) after vitrectomy for macular hole (MH) treatment using preoperative opti...

Fundus image segmentation via hierarchical feature learning.

Fundus Image Segmentation (FIS) is an essential procedure for the automated diagnosis of ophthalmic diseases. Recently, deep fully convolutional netwo...

A failure to learn object shape geometry: Implications for convolutional neural networks as plausible models of biological vision.

Here we examine the plausibility of deep convolutional neural networks (CNNs) as a theoretical framework for understanding biological vision in the co...