Ophthalmology

Refractive Surgery

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

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Artificial Intelligence-Guided Inverse Design of Deployable Thermo-Metamaterial Implants.

Current limitations in implant design often lead to trade-offs between minimally invasive surgery an...

Current trends in pharmaceutical industry: Post -CoVid-19 pandemic effects.

The pharmaceutical industry is undergoing a period of significant transformation. This is driven by ...

Analyzing the Effect of Surgical and Corneal Parameters on the Postoperative Refractive Outcomes of Smile in Myopic Eyes Based on Machine Learning.

PURPOSE: To analyze the influence of individual parameters on the postoperative refractive outcomes ...

A novel way to use cross-validation to measure connectivity by machine learning allows epilepsy surgery outcome prediction.

The rate of success of epilepsy surgery, ensuring seizure-freedom, is limited by the lack of epilept...

The Potential of SHAP and Machine Learning for Personalized Explanations of Influencing Factors in Myopic Treatment for Children.

The rising prevalence of myopia is a significant global health concern. Atropine eye drops are comm...

AI-Enhanced Healthcare: Integrating ChatGPT-4 in ePROs for Improved Oncology Care and Decision-Making: A Pilot Evaluation.

BACKGROUND: Since 2023, ChatGPT-4 has been impactful across several sectors including healthcare, wh...

Predicting the infecting dengue serotype from antibody titre data using machine learning.

The development of a safe and efficacious vaccine that provides immunity against all four dengue vir...

AI and Technology Enabled Clinical Workflow Redesign.

The rapid evolution of digital health technologies has significantly transformed health care deliver...

Finding the needle in the haystack of isokinetic knee data: Random Forest modelling improves information about ACLR-related deficiencies.

The difficulties of rehabilitation after anterior cruciate ligament (ACL) injuries, subsequent retur...

FPANet: Frequency-based video demoiréing using frame-level post alignment.

Moiré patterns, created by the interference between overlapping grid patterns in the pixel space, de...

Using artificial intelligence to predict post-operative outcomes in congenital heart surgeries: a systematic review.

INTRODUCTION: Congenital heart disease (CHD) represents the most common group of congenital anomalie...

Reliability of post-contrast deep learning-based highly accelerated cardiac cine MRI for the assessment of ventricular function.

OBJECTIVE: The total examination time can be reduced if high-quality two-dimensional (2D) cine image...

Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.

BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rat...

Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of case...

Machine Learning-Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study.

BACKGROUND AND OBJECTIVE: Early identification of post-stroke cognitive impairment (PSCI) is an impo...

Attention and dilated convolutions inclusive deep-CNN with multiplexed texture features to diagnose Pathological and High Myopia.

In today's era, precise and timely diagnosis of ocular diseases are crucial as these disorders jeopa...

Chemical-functional characterization of and and dietary supplementation in post-weaning pigs.

INTRODUCTION: As the livestock industry grapples with the need for sustainable land, maintaining pro...

Artificial intelligence applications in smile design dentistry: A scoping review.

PURPOSE: Artificial intelligence (AI) applications are growing in smile design and aesthetic procedu...

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