AIMC Topic: Cataract
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A Hybrid Global-Local Representation CNN Model for Automatic Cataract Grading.
IEEE journal of biomedical and health informatics
May 3, 2019
Cataract is one of the most serious eye diseases leading to blindness. Early detection and treatment can reduce the rate of blindness in cataract patients. However, the professional knowledge of ophthalmologists is necessary for the clinical cataract...
[Can Big Data change our practices?].
Journal francais d'ophtalmologie
Apr 9, 2019
The European Medicines Agency has defined Big Data by the "3 V's": Volume, Velocity and Variety. These large databases allow access to real life data on patient care. They are particularly suited for studies of adverse events and pharmacoepidemiology...
Determining optimal ultrasound percent on time with long-pulse torsional phacoemulsification.
Canadian journal of ophthalmology. Journal canadien d'ophtalmologie
Sep 11, 2018
OBJECTIVE: To evaluate the optimum percent on time for the most efficient lens fragment removal using long-pulse torsional ultrasound (US).
Exploiting ensemble learning for automatic cataract detection and grading.
Computer methods and programs in biomedicine
Oct 24, 2015
Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is one of the most common causes of visual impairment worldwide. Early diagnosis demands the expertise of trained healthcare professionals, which may present a...
Automatic Feature Learning to Grade Nuclear Cataracts Based on Deep Learning.
IEEE transactions on bio-medical engineering
Jun 11, 2015
GOAL: Cataracts are a clouding of the lens and the leading cause of blindness worldwide. Assessing the presence and severity of cataracts is essential for diagnosis and progression monitoring, as well as to facilitate clinical research and management...
Machine learning Reveals ATM and CNOT6L as critical factors in Cataract pathogenesis.
Experimental eye research
Aug 1, 2025
OBJECTIVE: Cataract, a common age-related blinding eye disease, has a complex pathogenesis. This study aims to identify key genes and potential mechanisms associated with cataracts, offering new targets and insights for its prevention and treatment.
Application of generative adversarial networks in the restoration of blurred optical coherence tomography images caused by optical media opacity in eyes.
BMJ open ophthalmology
May 26, 2025
PURPOSE: To assess the application of generative adversarial networks (GANs) to restore the blurred optical coherence tomography (OCT) images caused by optical media opacity in eyes.
CATALYZE: a deep learning approach for cataract assessment and grading on SS-OCT images.
Journal of cataract and refractive surgery
Mar 1, 2025
PURPOSE: To assess a new objective deep learning model cataract grading method based on swept-source optical coherence tomography (SS-OCT) scans provided by the Anterion.
Reply: Artificial intelligence chatbot and Academy Preferred Practice Pattern® Guidelines on cataract and glaucoma.
Journal of cataract and refractive surgery
Jun 1, 2024
Comment on: Artificial intelligence chatbot and Academy Preferred Practice Pattern ® Guidelines on cataract and glaucoma.
Journal of cataract and refractive surgery
Jun 1, 2024
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