Latest AI and machine learning research in laser surgery for healthcare professionals.
PURPOSE: This article is a scoping review of published and peer-reviewed articles using deep-learning (DL) applied to ultra-widefield (UWF) imaging. This study provides an overview of the published uses of DL and UWF imaging for the detection of ophthalmic and systemic diseases, generative image synthesis, quality assessment of images, and segmentation and localization of ophthalmic image features...
Surgical skill evaluation while performing minimally invasive surgeries is a highly complex task. It is important to objectively assess an individual's technical skills throughout surgical training to monitor progress and to intervene when skills are not commensurate with the year of training. The miniaturization of wireless wearable platforms integrated with sensor technology has made it possibl...
INTRODUCTION: Traditional bone surgery using saws and chisels is associated with direct contact of instruments with the bone causing friction, heat an...
PURPOSE: Ophthalmic surgery involves the manipulation of micron-level sized structures such as the internal limiting membrane where tactile sensation ...
Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health re...
INTRODUCTION: Procedures involving the external genitalia are the most common pediatric urologic operations. Our group identified excess instrumentati...
We sought to describe the development of the robotic urology program at Sindh Institute of Urology and Transplantation (SIUT) and the feasibility of t...
Currently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the preclinical stage. This study assessed the pupil lig...
The adoption of a valveless trocar system in robotic surgery has allowed for stable pneumoperitoneum and constant smoke evacuation. The reported bene...
External beam radiotherapy is aimed to precisely deliver a high radiation dose to malignancies, while optimally sparing surrounding healthy tissues. W...
Detection, diagnosis, and treatment of ophthalmic diseases depend on extraction of information (features and/or their dimensions) from the images. Dee...
Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has re...
To analyze operating room (OR) efficiency by evaluating fixed OR times for three common urologic robot-assisted procedures. Over a 24-month period, ...
OBJECTIVE: A retina optical coherence tomography (OCT) image differs from a traditional image due to its significant speckle noise, irregularity, and ...
An automatic assessment system for physical telerehabilitation could reduce the time and cost of treatments. But such assessment involves stochastic u...
With non-invasive and high-resolution properties, optical coherence tomography (OCT) has been widely used as a retinal imaging modality for the effect...
MOTIVATION: Training domain-specific named entity recognition (NER) models requires high quality hand curated gold standard datasets which are time-co...
This study is aimed at analyzing the important role of deep learning-based electrocardiograph (ECG) in the efficacy evaluation of radiofrequency ablat...
Toxoplasmosis is a zoonotic illness caused by . Those with a normal immune system normally recover without treatment. Immunocompromised individuals an...
BACKGROUND AND OBJECTIVE: Early fundus screening and timely treatment of ophthalmology diseases can effectively prevent blindness. Previous studies ju...