AIMC Topic: Cataract

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Automatic cataract grading methods based on deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The shortage of ophthalmologists in rural areas in China causes a lot of cataract patients not getting timely diagnosis and effective treatment. We develop an algorithm and platform to automatically diagnose and grade catara...

Automatic Cataract Classification Using Deep Neural Network With Discrete State Transition.

IEEE transactions on medical imaging
Cataract is the clouding of lens, which affects vision and it is the leading cause of blindness in the world's population. Accurate and convenient cataract detection and cataract severity evaluation will improve the situation. Automatic cataract dete...

A Hybrid Global-Local Representation CNN Model for Automatic Cataract Grading.

IEEE journal of biomedical and health informatics
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
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
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
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
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
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.