Refractive Surgery

FacePsy: An Open-Source Affective Mobile Sensing System -- Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings

Depression, a prevalent and complex mental health issue affecting millions worldwide, presents significant challenges for detection and monitoring. While facial expressions have shown promise in laboratory settings for identifying depression, their potential in real-world applications remains largely unexplored due to the difficulties in developing efficient mobile systems. In this study, we aim...

BrainSegFounder: Towards 3D Foundation Models for Neuroimage Segmentation

The burgeoning field of brain health research increasingly leverages artificial intelligence (AI) to interpret and analyze neurological data. This study introduces a novel approach towards the creation of medical foundation models by integrating a large-scale multi-modal magnetic resonance imaging (MRI) dataset derived from 41,400 participants in its own. Our method involves a novel two-stage pr...

Deep-Learning Approach for Tissue Classification using Acoustic Waves during Ablation with an Er:YAG Laser (Updated)

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to...

Forecasting Myopic Maculopathy Risk Over a Decade: Development and Validation of an Interpretable Machine Learning Algorithm.

PURPOSE: The purpose of this study was to develop and validate prediction model for myopic macular degeneration (MMD) progression in patients with hig...

Introducing a machine learning algorithm for delirium prediction-the Supporting SURgery with GEriatric Co-Management and AI project (SURGE-Ahead).

INTRODUCTION: Post-operative delirium (POD) is a common complication in older patients, with an incidence of 14-56%. To implement preventative procedu...

Ocular Biometric Components in Hyperopic Children and a Machine Learning-Based Model to Predict Axial Length.

PURPOSE: The purpose of this study was to investigate the development of optical biometric components in children with hyperopia, and apply a machine-...

An editorial on myopia control, mainly written by ChatGPT.

Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.

PURPOSE: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and dia...

[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].

To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The ...

Reshaping Wound Care: Evaluation of an Artificial Intelligence App to Improve Wound Assessment and Management.

This study evaluated the usability and effectiveness of an artificial intelligence application for wound assessment and management from a clinician-an...

MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering.

Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-specific tasks such as medical question answering (...

Identifying best fall-related balance factors and robotic-assisted gait training attributes in 105 post-stroke patients using clinical machine learning models.

BACKGROUND: Despite the promising effects of robot-assisted gait training (RAGT) on balance and gait in post-stroke rehabilitation, the optimal predic...

Prediction of early-phase cytomegalovirus pneumonia in post-stem cell transplantation using a deep learning model.

BACKGROUND: Diagnostic challenges exist for CMV pneumonia in post-hematopoietic stem cell transplantation (post-HSCT) patients, despite early-phase ra...

Enhancing Post-Surgical Wound Care in Anorectal Diseases: A Comparative Study of Advanced Convolutional Neural Network (CNN) Architectures for Image Classification and Analysis.

AIM: Anorectal diseases, often requiring surgical intervention and careful post-operative wound management, pose substantial challenges in healthcare....

Real-Time Monitoring for Aseptic Drilling: Lessons Learned from the Atacama Rover Astrobiology Drilling Studies Contamination Control Strategy and Implementation and Application to the Icebreaker Mars Life Detection Mission.

In 2019, the Atacama Rover Astrobiology Drilling Studies (ARADS) project field-tested an autonomous rover-mounted robotic drill prototype for a 6-Sol ...

[Deep Learning-Based Identification of Common Complication Features of Surgical Incisions].

OBJECTIVE: In recent years, due to the development of accelerated recovery after surgery and day surgery in the field of surgery, the average length-o...

2D Wavelet-Scalogram Deep-Learning for Seizures Pattern Identification in the Post-Hypoxic-Ischemic EEG of Preterm Fetal Sheep.

Neonatal seizures after an hypoxic-ischemic (HI) event in preterm newborns can contribute to neural injury and cause impaired brain development. Prete...

Artificial intelligence, machine learning, and deep learning in liver transplantation.

Liver transplantation (LT) is a life-saving treatment for individuals with end-stage liver disease. The management of LT recipients is complex, predom...

Robot-assisted radical cystectomy: Where we are in 2023.

Open radical cystectomy (ORC) is associated with high rates of perioperative morbidity and mortality, owing to its extensive surgical nature and the h...

A Review of the Role of Robotics in Surgery: To DaVinci and Beyond!

Since its inception in 1985, robotic surgery has evolved into a mainstream surgical approach that has become virtually synonymous with minimally invas...