Refractive Surgery

Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as...

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 d...

Artificial Intelligence on The Couch. Staying Human Post-AI.

This paper examines the human relationship to technology, and AI in particular, including the propos...

An editorial on myopia control, mainly written by ChatGPT.

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 component...

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 inci...

Computed tomography-based radiomics to predict early recurrence of hepatocellular carcinoma post-hepatectomy in patients background on cirrhosis.

BACKGROUND: The prognosis for hepatocellular carcinoma (HCC) in the presence of cirrhosis is unfavou...

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 hi...

[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 spot...

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 w...

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

Large Language Models (LLMs), although powerful in general domains, often perform poorly on domain-s...

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 mana...

Advanced Machine Learning Models for Predicting Post-Thrombolysis Hemorrhagic Transformation in Acute Ischemic Stroke Patients: A Systematic Review and Meta-Analysis.

Thrombolytic therapy is essential for acute ischemic stroke (AIS) management but poses a risk of he...

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 transplant...

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...

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 ...

[Saved myocardium in acute ST-segment elevation myocardial infarction post-reperfusion: Analysis by cardiac magnetic resonance].

OBJECTIVE: To quantify by cardiovascular magnetic resonance the salvaged myocardium in the myocardiu...

[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 sur...

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 ...

Feature extraction of time series data on functional near-infrared spectroscopy and comparison of deep learning performance for classifying patients with Alzheimer's-related mild cognitive impairment: a post-hoc analysis of a diagnostic interventional trial.

OBJECTIVE: This study aimed to define a method of classifying patients with mild cognitive impairmen...

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. ...