Refractive Surgery

Development and evaluation of a deep neural network model for orthokeratology lens fitting.

PURPOSE: To optimise the precision and efficacy of orthokeratology, this investigation evaluated a d...

Clinician perceptions of a novel wearable robotic hand orthosis for post-stroke hemiparesis.

PURPOSE: Wearable robotic devices are currently being developed to improve upper limb function for i...

Surface electromyography vs clinical outcome measures after robot-assisted gait training in patients with spinal cord injury after post-acute phase of rehabilitation.

INTRODUCTION AND OBJECTIVE: Surface electromyography (sEMG) measurements are a valid method for subl...

Artificial Intelligence in Facial Plastics and Reconstructive Surgery.

Artificial intelligence (AI), particularly computer vision and large language models, will impact fa...

Machine Learning Based Prediction of Post-operative Infrarenal Endograft Apposition for Abdominal Aortic Aneurysms.

OBJECTIVE: Challenging infrarenal aortic neck characteristics have been associated with an increased...

Quantitative assessment of colour fundus photography in hyperopia children based on artificial intelligence.

OBJECTIVES: This study aimed to quantitatively evaluate optic nerve head and retinal vascular parame...

Automated eyeball volume measurement based on CT images using neural network-based segmentation and simple estimation.

With the increase in the dependency on digital devices, the incidence of myopia, a precursor of vari...

Deep Learning-Enhanced Internet of Things for Activity Recognition in Post-Stroke Rehabilitation.

Wearable sensors provide a more effective means of activity monitoring and management by recording p...

Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.

Machine learning offers great potential for automated prediction of post-stroke symptoms and their r...

Artificial Intelligence Application in Skull Bone Fracture with Segmentation Approach.

This study aims to evaluate an AI model designed to automatically classify skull fractures and visua...

A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

PURPOSE: To examine whether there is a significant difference in image quality between the deep lear...

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have d...

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...

Commentary on "develop a radiomics-based machine learning model to predict the stone-free rate post-percutaneous nephrolithotomy".

A novel virtual robotic platform for controlling six degrees of freedom assistive devices with body-machine interfaces.

Body-machine interfaces (BoMIs)-systems that control assistive devices (e.g., a robotic manipulator)...

Enhancing post-training evaluation of annual performance agreement training: A fusion of fsQCA and artificial neural network approach.

This study aims to enhance the post-training evaluation of the annual performance agreement (APA) tr...

Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care.

This article proposes a framework for examining the ethical and legal concerns for using artificial ...

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIR...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, en...

Post-stroke hand gesture recognition via one-shot transfer learning using prototypical networks.

BACKGROUND: In-home rehabilitation systems are a promising, potential alternative to conventional th...

Quantifying social capital creation in post-disaster recovery aid in Indonesia: methodological innovation by an AI-based language model.

Smooth interaction with a disaster-affected community can create and strengthen its social capital, ...