Ophthalmology

Algorithmic bias: Social science research integration through the 3-D Dependable AI Framework.

Algorithmic bias has emerged as a critical challenge in the age of responsible production of artific...

Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is l...

Double vision: 2D and 3D mosquito trajectories can be as valuable for behaviour analysis via machine learning.

BACKGROUND: Mosquitoes are carriers of tropical diseases, thus demanding a comprehensive understandi...

Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization.

Fairness (also known as equity interchangeably) in machine learning is important for societal well-b...

Computer Vision for Gait Assessment in Cerebral Palsy: Metric Learning and Confidence Estimation.

Assessing the motor impairments of individuals with neurological disorders holds significant importa...

Quantum machine learning in ophthalmology.

Efficient pyramid channel attention network for pathological myopia recognition with pretraining-and-finetuning.

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, th...

When Trustworthiness Meets Face: Facial Design for Social Robots.

As a technical application in artificial intelligence, a social robot is one of the branches of robo...

TransKinect: a computer vision and machine learning clinical decision support system for automatic independent wheelchair transfer technique assessment.

BACKGROUND: Physical and occupational therapists provide routine care for manual wheelchair users an...

Uncertainty-aware multiple-instance learning for reliable classification: Application to optical coherence tomography.

Deep learning classification models for medical image analysis often perform well on data from scann...

Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children's educational robotics activities.

In technology education, there has been a paradigmatic shift towards student-centered approaches suc...

Optical imaging for diabetic retinopathy diagnosis and detection using ensemble models.

Diabetes, characterized by heightened blood sugar levels, can lead to a condition called Diabetic Re...

Applications of artificial intelligence in diagnosis of uncommon cystoid macular edema using optical coherence tomography imaging: A systematic review.

Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and ...

Robot-assisted system for non-invasive wide-range flexible eye positioning and tracking in particle radiotherapy.

Particle (proton, carbon ion, or others) radiotherapy for ocular tumors is highly dependent on preci...

Assessing AI receptivity through a persuasion knowledge lens.

Understanding human-artificial intelligence (AI) interactions is a growing academic interest. This a...

Enhanced Hybrid Vision Transformer with Multi-Scale Feature Integration and Patch Dropping for Facial Expression Recognition.

Convolutional neural networks (CNNs) have made significant progress in the field of facial expressio...

Advancements in computer vision and pathology: Unraveling the potential of artificial intelligence for precision diagnosis and beyond.

The integration of computer vision into pathology through slide digitalization represents a transfor...

Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostate...

Automated monitoring of brush use in dairy cattle.

Access to brushes allows for natural scratching behaviors in cattle, especially in confined indoor s...

Tongue image fusion and analysis of thermal and visible images in diabetes mellitus using machine learning techniques.

The study aimed to achieve the following objectives: (1) to perform the fusion of thermal and visibl...

Enhancing fall risk assessment: instrumenting vision with deep learning during walks.

BACKGROUND: Falls are common in a range of clinical cohorts, where routine risk assessment often com...