Ophthalmology

Eye contact during joint attention with a humanoid robot modulates oscillatory brain activity.

Eye contact established by a human partner has been shown to affect various cognitive processes of the receiver. However, little is known about humans' responses to eye contact established by a humanoid robot. Here, we aimed at examining humans' oscillatory brain response to eye contact with a humanoid robot. Eye contact (or lack thereof) was embedded in a gaze-cueing task and preceded the phase o...

Full-color retinal-projection near-eye display using a multiplexing-encoding holographic method.

We propose a novel method to construct an optical see-through retinal-projection near-eye display using the Maxwellian view and a holographic method. To provide a dynamic full-color virtual image, a single phase-only spatial light modulator (SLM) was employed in conjunction with a multiplexing-encoding holographic method. Holographic virtual images can be directly projected onto the retina using a...

Detection of glaucoma using retinal fundus images: A comprehensive review.

Content-based image analysis and computer vision techniques are used in various health-care systems to detect the diseases. The abnormalities in a hum...

Use of Telepresence Robots in Glaucoma Patient Education.

PRCIS: Telepresence robots (TR) present the versatility to effectively provide remote educational sessions for patients affected by glaucoma to improv...

Artificial intelligence and complex statistical modeling in glaucoma diagnosis and management.

PURPOSE OF REVIEW: The field of artificial intelligence has grown exponentially in recent years with new technology, methods, and applications emergin...

Improvement of Multiple Generations of Intraocular Lens Calculation Formulae with a Novel Approach Using Artificial Intelligence.

PURPOSE: Cataract surgery is the most common eye surgery. Appropriate optimization of intraocular lens (IOL) calculation formulae can result in improv...

Artificial Intelligence to Reduce Ocular Health Disparities: Moving From Concept to Implementation.

An ecologically motivated image dataset for deep learning yields better models of human vision.

Deep neural networks provide the current best models of visual information processing in the primate brain. Drawing on work from computer vision, the ...

Correction for the Influence of Cataract on Macular Pigment Measurement by Autofluorescence Technique Using Deep Learning.

PURPOSE: Measurements of macular pigment optical density (MPOD) by the autofluorescence technique yield underestimations of actual values in eyes with...

The human visual system and CNNs can both support robust online translation tolerance following extreme displacements.

Visual translation tolerance refers to our capacity to recognize objects over a wide range of different retinal locations. Although translation is per...

Deep Learning Detection of Sea Fan Neovascularization From Ultra-Widefield Color Fundus Photographs of Patients With Sickle Cell Hemoglobinopathy.

IMPORTANCE: Adherence to screening for vision-threatening proliferative sickle cell retinopathy is limited among patients with sickle cell hemoglobino...

Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.

BACKGROUND: Ocular changes are traditionally associated with only a few hepatobiliary diseases. These changes are non-specific and have a low detectio...

Simultaneous laparoscopic nephroureterectomy and robot-assisted anterior pelvic exenteration with intracorporeal ileal conduit urinary diversion: step-by-step video-illustrated technique.

INTRODUCTION:: One of the most remarkable characteristics of urothelial carcinomas is multifocality. However, occurrence of synchronous bladder cancer...

Artificial intelligence: from the retina to the brain.

Artificial Intelligence and Clinical Decision Making: The New Nature of Medical Uncertainty.

Estimates in a 1989 study indicated that physicians in the United States were unable to reach a diagnosis that accounted for their patient's symptoms ...

Referral for disease-related visual impairment using retinal photograph-based deep learning: a proof-of-concept, model development study.

BACKGROUND: In current approaches to vision screening in the community, a simple and efficient process is needed to identify individuals who should be...

Explainable Deep Learning Reproduces a 'Professional Eye' on the Diagnosis of Internal Disorders in Persimmon Fruit.

Recent rapid progress in deep neural network techniques has allowed recognition and classification of various objects, often exceeding the performance...

The 'Digital Twin' to enable the vision of precision cardiology.

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about in...

Smartphone-based diabetic macula edema screening with an offline artificial intelligence.

BACKGROUND: Diabetic macular edema (DME) is a sight-threatening condition that needs regular examinations and remedies. Optical coherence tomography (...

New perspectives in the prediction of postoperative complications for high-risk ulcerative colitis patients: machine learning preliminary approach.

OBJECTIVE: Patients with acute severe and medical refractory ulcerative colitis have a high risk of postoperative complications after total abdominal ...