Laser Surgery

Ocular Diseases Detection using Recent Deep Learning Techniques.

Early fundus screening is a cost-effective and efficient approach to reduce ophthalmic disease-related blindness in ophthalmology. Manual evaluation is time-consuming. Ophthalmic disease detection studies have shown interesting results thanks to the advancement in deep learning techniques, but the majority of them are limited to a single disease. In this paper we propose the study of various deep ...

Updates in deep learning research in ophthalmology.

Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered significant attention due to the availability of large amounts of data and digitized ocular images. Currently, AI in Ophthalmology is mainly focused on improving disease classification and supporting decision-making when treating ophthalmic dise...

Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

PURPOSE OF REVIEW: The purpose of this review is to provide an overview of healthcare standards and their relevance to multiple ophthalmic workflows, ...

Artificial intelligence and ophthalmic surgery.

PURPOSE OF REVIEW: Artificial intelligence and deep learning have become important tools in extracting data from ophthalmic surgery to evaluate, teach...

Real-world validation of artificial intelligence algorithms for ophthalmic imaging.

Artificial intelligence in ophthalmology: Optimization of machine learning for ophthalmic care and research.

A Deep Learning Model for Screening Multiple Abnormal Findings in Ophthalmic Ultrasonography (With Video).

PURPOSE: The purpose of this study was to construct a deep learning system for rapidly and accurately screening retinal detachment (RD), vitreous deta...

Deep learning-based detection of hepatobiliary disorders in ophthalmic imaging.

[Urology].

Over the last year, urologic progress remains driven by the quick technologic evolution, with a focus on Laser and robotics. The latter appears to pot...

Multiclass retinal disease classification and lesion segmentation in OCT B-scan images using cascaded convolutional networks.

Disease classification and lesion segmentation of retinal optical coherence tomography images play important roles in ophthalmic computer-aided diagno...

Robot-Assisted Nephrectomy Using the Newly Developed Single-Port Robotic Surgical System: A Feasibility Study in Porcine Model.

To evaluate the feasibility and safety of the single-port robotic platform by performing nephrectomy in live porcine model. Robotic nephrectomy was...

Machine learning in the optimization of robotics in the operative field.

PURPOSE OF REVIEW: The increasing use of robotics in urologic surgery facilitates collection of 'big data'. Machine learning enables computers to infe...

Clinical applications of artificial intelligence in urologic oncology.

PURPOSE OF REVIEW: This review aims to shed light on recent applications of artificial intelligence in urologic oncology.

A novelty route for smartphone-based artificial intelligence approach to ophthalmic screening.

Artificial intelligence (AI) has been widely applied in the medical field and achieved enormous milestones in helping specialists to make diagnosis an...

Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.

IMPORTANCE: Recent studies have demonstrated the successful application of artificial intelligence (AI) for automated retinal disease diagnostics but ...

Accelerating ophthalmic artificial intelligence research: the role of an open access data repository.

PURPOSE OF REVIEW: Artificial intelligence has already provided multiple clinically relevant applications in ophthalmology. Yet, the explosion of nons...

Fundamentals of artificial intelligence for ophthalmologists.

PURPOSE OF REVIEW: As artificial intelligence continues to develop new applications in ophthalmic image recognition, we provide here an introduction f...

A V-Net Based Deep Learning Model for Segmentation and Classification of Histological Images of Gastric Ablation.

Gastric motility disorders are associated with bioelectrical abnormalities in the stomach. Recently, gastric ablation has emerged as a potential thera...

Deep Learning with Skip Connection Attention for Choroid Layer Segmentation in OCT Images.

Since the thickness and shape of the choroid layer are indicators for the diagnosis of several ophthalmic diseases, the choroid layer segmentation is ...

Retinal blood vessel segmentation based on Densely Connected U-Net.

The segmentation of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. This paper proposes a ne...