Laser Surgery

Transition from da Vinci to Versius robotic surgical system: initial experience and outcomes of over 100 consecutive procedures.

We sought to describe the development of the robotic urology program at Sindh Institute of Urology and Transplantation (SIUT) and the feasibility of transitioning from the da Vinci to Versius robotic systems. The SIUT robotics program began in 2017 utilizing the da Vinci Si robotic system, transitioning to the Versius system in 2021. Retrospective review of our quality assurance database was perfo...

Machine learning for comprehensive prediction of high risk for Alzheimer's disease based on chromatic pupilloperimetry.

Currently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the preclinical stage. This study assessed the pupil light reflex (PLR) for focal red and blue light stimuli in central and peripheral retina in 125 cognitively normal middle age subjects (45-71 years old) at high risk for AD due to a family history of the disease (FH+), and 61 age-similar subjects with n...

The Role of AirSeal in Robotic Urologic Surgery: A Systematic Review.

The adoption of a valveless trocar system in robotic surgery has allowed for stable pneumoperitoneum and constant smoke evacuation. The reported bene...

Deep learning for dose assessment in radiotherapy by the super-localization of vaporized nanodroplets in high frame rate ultrasound imaging.

External beam radiotherapy is aimed to precisely deliver a high radiation dose to malignancies, while optimally sparing surrounding healthy tissues. W...

A lightweight deep learning model for automatic segmentation and analysis of ophthalmic images.

Detection, diagnosis, and treatment of ophthalmic diseases depend on extraction of information (features and/or their dimensions) from the images. Dee...

New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology.

Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has re...

Analysis of Operating Room Efficiency During Robot-Assisted Urologic Surgeries Utilizing Fixed (Nonprocedural) Operative Times.

To analyze operating room (OR) efficiency by evaluating fixed OR times for three common urologic robot-assisted procedures. Over a 24-month period, ...

Towards more efficient ophthalmic disease classification and lesion location via convolution transformer.

OBJECTIVE: A retina optical coherence tomography (OCT) image differs from a traditional image due to its significant speckle noise, irregularity, and ...

Automatic Evaluation of Motor Rehabilitation Exercises Based on Deep Mixture Density Neural Networks.

An automatic assessment system for physical telerehabilitation could reduce the time and cost of treatments. But such assessment involves stochastic u...

Recent Advanced Deep Learning Architectures for Retinal Fluid Segmentation on Optical Coherence Tomography Images.

With non-invasive and high-resolution properties, optical coherence tomography (OCT) has been widely used as a retinal imaging modality for the effect...

Effects of data and entity ablation on multitask learning models for biomedical entity recognition.

MOTIVATION: Training domain-specific named entity recognition (NER) models requires high quality hand curated gold standard datasets which are time-co...

Deep Learning-Based Electrocardiograph in Evaluating Radiofrequency Ablation for Rapid Arrhythmia.

This study is aimed at analyzing the important role of deep learning-based electrocardiograph (ECG) in the efficacy evaluation of radiofrequency ablat...

Machine Learning of ZnO Interaction with Immunoglobulins and Blood Proteins in Medicine.

Toxoplasmosis is a zoonotic illness caused by . Those with a normal immune system normally recover without treatment. Immunocompromised individuals an...

BFENet: A two-stream interaction CNN method for multi-label ophthalmic diseases classification with bilateral fundus images.

BACKGROUND AND OBJECTIVE: Early fundus screening and timely treatment of ophthalmology diseases can effectively prevent blindness. Previous studies ju...

An Efficient Stacked Deep Transfer Learning Model for Automated Diagnosis of Lyme Disease.

Lyme disease is one of the most common vector-borne infections. It typically causes cardiac illnesses, neurologic illnesses, musculoskeletal disorders...

Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.

On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intellige...

Arterial enhancing local tumor progression detection on CT images using convolutional neural network after hepatocellular carcinoma ablation: a preliminary study.

To evaluate the performance of a deep convolutional neural network (DCNN) in detecting local tumor progression (LTP) after tumor ablation for hepatoce...

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify...

PCAT-UNet: UNet-like network fused convolution and transformer for retinal vessel segmentation.

The accurate segmentation of retinal vessels images can not only be used to evaluate and monitor various ophthalmic diseases, but also timely reflect ...

A novel graph convolutional neural network for predicting interaction sites on protein kinase inhibitors in phosphorylation.

Protein kinase-inhibitor interactions are key to the phosphorylation of proteins involved in cell proliferation, differentiation, and apoptosis, which...