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Cataract

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Detecting visually significant cataract using retinal photograph-based deep learning.

Nature aging
Age-related cataracts are the leading cause of visual impairment among older adults. Many significant cases remain undiagnosed or neglected in communities, due to limited availability or accessibility to cataract screening. In the present study, we r...

Customization of a passive surgical support robot to specifications for ophthalmic surgery and preliminary evaluation.

Japanese journal of ophthalmology
PURPOSE: To customize a passive surgery support robot for ophthalmic surgery and preliminarily evaluate its performance.

The effect of optical degradation from cataract using a new Deep Learning optical coherence tomography segmentation algorithm.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: To assess the validity of the results of a freely available online Deep Learning segmentation tool and its sensitivity to noise introduced by cataract.

Deep learning-based analysis of infrared fundus photography for automated diagnosis of diabetic retinopathy with cataracts.

Journal of cataract and refractive surgery
PURPOSE: To develop deep learning-based networks for the diagnosis of diabetic retinopathy (DR) with cataracts based on infrared fundus images.

Feasibility of an artificial intelligence phone call for postoperative care following cataract surgery in a diverse population: two phase prospective study protocol.

BMJ open ophthalmology
INTRODUCTION: Artificial intelligence (AI) development has led to improvements in many areas of medicine. Canada has workforce pressures in delivering cataract care. A potential solution is using AI technology that can automate care delivery, increas...

Talking technology: exploring chatbots as a tool for cataract patient education.

Clinical & experimental optometry
CLINICAL RELEVANCE: Worldwide, millions suffer from cataracts, which impair vision and quality of life. Cataract education improves outcomes, satisfaction, and treatment adherence. Lack of health literacy, language and cultural barriers, personal pre...

Using Natural Language Processing to Identify Different Lens Pathology in Electronic Health Records.

American journal of ophthalmology
PURPOSE: Nearly all published ophthalmology-related Big Data studies rely exclusively on International Classification of Diseases (ICD) billing codes to identify patients with particular ocular conditions. However, inaccurate or nonspecific codes may...

Deep learning model for extensive smartphone-based diagnosis and triage of cataracts and multiple corneal diseases.

The British journal of ophthalmology
AIM: To develop an artificial intelligence (AI) algorithm that diagnoses cataracts/corneal diseases from multiple conditions using smartphone images.