Ophthalmology

Refractive Surgery

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

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Robotic Assessment of Upper Limb Function in a Nonhuman Primate Model of Chronic Stroke.

Stroke is a leading cause of death and disability worldwide and survivors are frequently left with l...

Pathological myopia classification with simultaneous lesion segmentation using deep learning.

BACKGROUND AND OBJECTIVES: Pathological myopia (PM) is the seventh leading cause of blindness, with ...

Comparison of deep learning synthesis of synthetic CTs using clinical MRI inputs.

There has been substantial interest in developing techniques for synthesizing CT-like images from MR...

Development and validation of a deep learning system to screen vision-threatening conditions in high myopia using optical coherence tomography images.

BACKGROUND/AIMS: To apply deep learning technology to develop an artificial intelligence (AI) system...

Tualang honey versus steroid impregnated nasal dressing following endoscopic sinus surgery: a randomized controlled trial.

OBJECTIVES: Recurrence rate of nasal polyps is high following endoscopic sinus surgery. To improve t...

Prediction of in-hospital mortality in patients on mechanical ventilation post traumatic brain injury: machine learning approach.

BACKGROUND: The study aimed to introduce a machine learning model that predicts in-hospital mortalit...

A deep learning approach for identifying cancer survivors living with post-traumatic stress disorder on Twitter.

BACKGROUND: Emotions after surviving cancer can be complicated. The survivors may have gained new st...

Shoulder hydrodilatation for primary, post-traumatic and post-operative adhesive capsulitis.

BACKGROUND: Adhesive capsulitis (frozen shoulder) is characterised by pain and loss of range of moti...

Predicting Post-Concussion Symptom Recovery in Adolescents Using a Novel Artificial Intelligence.

This pilot study explores the possibility of predicting post-concussion symptom recovery at one week...

Post-DAE: Anatomically Plausible Segmentation via Post-Processing With Denoising Autoencoders.

We introduce Post-DAE, a post-processing method based on denoising autoencoders (DAE) to improve the...

The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis.

Recently, deep learning frameworks have rapidly become the main methodology for analyzing medical im...

The effect of PARO robotic seals for hospitalized patients with dementia: A feasibility study.

Robotic seals have been studied in long-term care settings; though, no studies of patients with deme...

Relationships between motor and cognitive functions and subsequent post-stroke mood disorders revealed by machine learning analysis.

Mood disorders (e.g. depression, apathy, and anxiety) are often observed in stroke patients, exhibit...

Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.

Understanding predator-prey interactions and food web dynamics is important for ecosystem-based mana...

Predictive Factors for Blood Transfusion after Total Knee Arthroplasty.

 The present paper aims to (1) verify the incidence and volume of blood transfusion among patients ...

Pediatric Adenoidectomy: A Comparative Study Between Cold Curettage and Coblation Technique.

The objective of the study was to assess endoscopic coblation adenoidectomy and conventional cold cu...

Deep Learning Applied to Vegetation Identification and Removal Using Multidimensional Aerial Data.

When performing structural inspection, the generation of three-dimensional (3D) point clouds is a co...

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