Ophthalmology

Refractive Surgery

Latest AI and machine learning research in refractive surgery for healthcare professionals.

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Predicting osteoporotic fractures post-vertebroplasty: a machine learning approach with a web-based calculator.

PURPOSE: The aim of this study was to develop and validate a machine learning (ML) model for predict...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

This study aimed to compare the accuracy of IFN-Ï„ stimulated gene abundance (ISGs) in peripheral blo...

Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment.

Clinical trials involving systemic neoadjuvant treatments in breast cancer aim to shrink tumors befo...

Machine learning for predicting elective fertility preservation outcomes.

This retrospective study applied machine-learning models to predict treatment outcomes of women unde...

Developing and validating a clinlabomics-based machine-learning model for early detection of retinal detachment in patients with high myopia.

BACKGROUND: Retinal detachment (RD) is a vision-threatening disorder of significant severity. Indivi...

Exploring post-COVID-19 health effects and features with advanced machine learning techniques.

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a rang...

Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-C...

Artificial intelligence and smile design: An e-Delphi consensus statement of ethical challenges.

PURPOSE: Smile design software increasingly relies on artificial intelligence (AI). However, using A...

Detecting white spot lesions on post-orthodontic oral photographs using deep learning based on the YOLOv5x algorithm: a pilot study.

BACKGROUND: Deep learning model trained on a large image dataset, can be used to detect and discrimi...

The gut microbiome associates with phenotypic manifestations of post-acute COVID-19 syndrome.

The mechanisms underlying the many phenotypic manifestations of post-acute COVID-19 syndrome (PACS) ...

Socially Assistive Robot for Stroke Rehabilitation: A Long-Term in-the-Wild Pilot Randomized Controlled Trial.

Socially assistive robots (SARs) have been suggested as a platform for post-stroke training. It is n...

Cataract-1K Dataset for Deep-Learning-Assisted Analysis of Cataract Surgery Videos.

In recent years, the landscape of computer-assisted interventions and post-operative surgical video ...

DeepDynaForecast: Phylogenetic-informed graph deep learning for epidemic transmission dynamic prediction.

In the midst of an outbreak or sustained epidemic, reliable prediction of transmission risks and pat...

Supervised machine learning for the prediction of post-operative clinical outcomes of hip and knee replacements: a review.

Prediction models are being increasingly used in the medical field to identify risk factors and poss...

Duodenal papilla radiomics-based prediction model for post-ERCP pancreatitis using machine learning: a retrospective multicohort study.

BACKGROUND AND AIMS: The duodenal papillae are the primary and essential pathway for ERCP, greatly d...

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study.

BACKGROUND AND AIMS: The impact of various categories of information on the prediction of post-ERCP ...

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

Individual muscle segmentation is the process of partitioning medical images into regions representi...

Uses and limitations of artificial intelligence for oncology.

Modern artificial intelligence (AI) tools built on high-dimensional patient data are reshaping oncol...

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