Refractive Surgery

Brain Network Organization Following Post-Stroke Neurorehabilitation.

Brain network analysis can offer useful information to guide the rehabilitation of post-stroke patients. We applied functional network connection models based on multiplex-multilayer network analysis (MMN) to explore functional network connectivity changes induced by robot-aided gait training (RAGT) using the Ekso, a wearable exoskeleton, and compared it to conventional overground gait training (C...

A simulation study to investigate the use of concentric tube robots for epilepsy surgery.

PURPOSE: Patients with pharmacoresistant refractory epilepsy may require epilepsy surgery to prevent future seizure occurrences. Conventional surgery consists of a large craniotomy with straight rigid tools with associated outcomes of morbidity, large tissue resections, and long post-operative recovery times. Concentric tube robots have recently been developed as a promising application to neurosu...

Developing basic robotic skills using virtual reality simulation and automated assessment tools: a multidisciplinary robotic virtual reality-based curriculum using the Da Vinci Skills Simulator and tracking progress with the Intuitive Learning platform.

This study sought to develop basic robotic surgical skills among surgical trainees across multiple specialties using a VR-based curriculum and provide...

Nerve spare robot assisted laparoscopic prostatectomy with amniotic membranes: medium term outcomes.

dHACM is a source of factors including cytokines that allow anti-inflammatory and proliferative elements to be utilized for wound and ulcer management...

Preoperative oral carbohydrate loading: Effects on intraoperative blood glucose levels, post-operative nausea and vomiting, and intensive care unit stay.

BACKGROUND AND AIMS: Preoperative fasting imparts safety to patients from aspiration of gastric contents, but undue fasting may predispose to hypoglyc...

Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies.

Chronic exertional compartment syndrome (CECS) is a condition occurring most frequently in the lower limbs and often requires corrective surgery to al...

Elevated Levels of Urinary Biomarkers TIMP-2 and IGFBP-7 Predict Acute Kidney Injury in Neonates after Congenital Heart Surgery.

 This article investigated the utility of urine biomarkers tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding pr...

A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure.

Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Gener...

Emergence of flexible technology in developing advanced systems for post-stroke rehabilitation: a comprehensive review.

Stroke is one of the most common neural disorders, which causes physical disabilities and motor impairments among its survivors. Several technologies ...

Does prior transurethral resection of prostate affect the functional and oncological outcomes of robot-assisted radical prostatectomy? A matched-pair analysis.

Robot-assisted radical prostatectomy (RARP) is challenging in men with prior history of transurethral resection of the prostate (TURP). Few studies an...

DNA methylation-based classification of malformations of cortical development in the human brain.

Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definit...

The shallow of your smile: the ethics of expressive vocal deep-fakes.

Rapid technological advances in artificial intelligence are creating opportunities for real-time algorithmic modulations of a person's facial and voca...

Postsurgery Classification of Best-Corrected Visual Acuity Changes Based on Pterygium Characteristics Using the Machine Learning Technique.

INTRODUCTION: Early detection of visual symptoms in pterygium patients is crucial as the progression of the disease can cause visual disruption and co...

A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning.

This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-ex...

Autonomous Thermal Vision Robotic System for Victims Recognition in Search and Rescue Missions.

Technological breakthroughs in recent years have led to a revolution in fields such as Machine Vision and Search and Rescue Robotics (SAR), thanks to ...

Robotic repair of post-oesophagectomy hiatal hernia.

Diaphragmatic hiatal hernia is a potential complication of oesophagectomy in cancer patients. Over the past decades, laparoscopy has become the prefer...

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 implanta...

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...

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft failure. Here we sought an objective, quantitative...

Automated post-operative brain tumour segmentation: A deep learning model based on transfer learning from pre-operative images.

Automated brain tumour segmentation from post-operative images is a clinically relevant yet challenging problem. In this study, an automated method fo...