Refractive Surgery

Comparative Analysis on Machine Learning and Deep Learning to Predict Post-Induction Hypotension.

Hypotensive events in the initial stage of anesthesia can cause serious complications in the patient...

Effects of Exoskeletal Lower Limb Robot Training on the Activities of Daily Living in Stroke Patients: Retrospective Pre-Post Comparison Using Propensity Score Matched Analysis.

PURPOSE: There is limited evidence of gait training using newly developed exoskeletal lower limb rob...

Digital application developed to evaluate functional results following robot-assisted radical prostatectomy: App for prostate cancer.

INTRODUCTION: Mobile applications ("apps") developed for smartphones and tablets are increasingly us...

The prospect of machine learning in predicting post-lithotripsy outcomes.

Changes in functional connectivity after theta-burst transcranial magnetic stimulation for post-traumatic stress disorder: a machine-learning study.

Intermittent theta burst stimulation (iTBS) is a novel treatment approach for post-traumatic stress ...

Improved myocardial perfusion PET imaging using artificial neural networks.

Myocardial perfusion (MP) PET imaging plays a key role in risk assessment and stratification of pati...

The ReWalk ReStore™ soft robotic exosuit: a multi-site clinical trial of the safety, reliability, and feasibility of exosuit-augmented post-stroke gait rehabilitation.

BACKGROUND: Atypical walking in the months and years after stroke constrain community reintegration ...

Social media forensics applied to assessment of post-critical incident social reaction: The case of the 2017 Manchester Arena terrorist attack.

Forensic science is constantly evolving and transforming, reflecting the numerous technological inno...

Implementation of a Novel Bluetooth Technology for Remote Deep Brain Stimulation Programming: The Pre- and Post-COVID-19 Beijing Experience.

A machine learning model that classifies breast cancer pathologic complete response on MRI post-neoadjuvant chemotherapy.

BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complet...

Motion Sensors-Based Machine Learning Approach for the Identification of Anterior Cruciate Ligament Gait Patterns in On-the-Field Activities in Rugby Players.

Anterior cruciate ligament (ACL) injuries are common among athletes. Despite a successful return to ...

Prediction of in-hospital mortality in patients with post traumatic brain injury using National Trauma Registry and Machine Learning Approach.

BACKGROUND: The use of machine learning techniques to predict diseases outcomes has grown significan...

Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network.

In this paper, we demonstrate the feasibility and performance of deep residual neural networks for v...

The fourier M2 robotic machine combined with occupational therapy on post-stroke upper limb function and independence-related quality of life: A randomized clinical trial.

Most post-stroke patients experience upper limb functionality challenges. Emergent therapies using u...

Deep learning enables automated localization of the metastatic lymph node for thyroid cancer on I post-ablation whole-body planar scans.

The accurate detection of radioactive iodine-avid lymph node (LN) metastasis on I post-ablation whol...

Enhancing the Surface Properties of a Bioengineered Anterior Cruciate Ligament Matrix for Use with Point-of-Care Stem Cell Therapy.

We have previously developed a poly(-lactic) acid (PLLA) bioengineered anterior cruciate ligament (A...

Semi-supervised labelling of the femur in a whole-body post-mortem CT database using deep learning.

A deep learning pipeline was developed and used to localize and classify a variety of implants in th...

Multi-view deep learning for rigid gas permeable lens base curve fitting based on Pentacam images.

Many studies in the rigid gas permeable (RGP) lens fitting field have focused on providing the best ...

Association Rule Learning Is an Easy and Efficient Method for Identifying Profiles of Traumas and Stressors that Predict Psychopathology in Disaster Survivors: The Example of Sri Lanka.

Research indicates that psychopathology in disaster survivors is a function of both experienced trau...

Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography.

This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical ...

Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.

Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathol...