AIMC Topic: Cataract

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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.

Phase recognition in manual Small-Incision cataract surgery with MS-TCN + + on the novel SICS-105 dataset.

Scientific reports
Manual Small-Incision Cataract Surgery (SICS) is a prevalent technique in low- and middle-income countries (LMICs) but understudied with respect to computer assisted surgery. This prospective cross-sectional study introduces the first SICS video data...

Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.

Computers in biology and medicine
The variability in image modalities presents significant challenges in medical image classification, as traditional deep learning models often struggle to adapt to different image types, leading to suboptimal performance across diverse datasets. This...

Artificial intelligence support improves diagnosis accuracy in anterior segment eye diseases.

Scientific reports
CorneAI, a deep learning model designed for diagnosing cataracts and corneal diseases, was assessed for its impact on ophthalmologists' diagnostic accuracy. In the study, 40 ophthalmologists (20 specialists and 20 residents) classified 100 images, in...

Galactose-Induced Cataracts in Rats: A Machine Learning Analysis.

International journal of medical sciences
Rat models are widely used to study cataracts due to their cost-effectiveness and prominent physiological and genetic similarities to humans The objective of this study was to identify genes involved in cataractogenesis due to galactose exposure in ...

Deep learning-based assessment of missense variants in the gene presented with bilateral congenital cataract.

BMJ open ophthalmology
OBJECTIVE: We compared the protein structure and pathogenicity of clinically relevant variants of the gene with AlphaFold2 (AF2), Alpha Missense (AM), and ThermoMPNN for the first time.

Diabetes and Cataracts Development-Characteristics, Subtypes and Predictive Modeling Using Machine Learning in Romanian Patients: A Cross-Sectional Study.

Medicina (Kaunas, Lithuania)
Diabetes has become a global epidemic, contributing to significant health challenges due to its complications. Among these, diabetes can affect sight through various mechanisms, emphasizing the importance of early identification and management of vi...

Prediction of Visual Acuity After Cataract Surgery by Deep Learning Methods Using Clinical Information and Color Fundus Photography.

Current eye research
PURPOSE: To examine the performance of deep-learning models that predicts the visual acuity after cataract surgery using preoperative clinical information and color fundus photography (CFP).

Diagnosing Cataracts in the Digital Age: A Survey on AI, Metaverse, and Digital Twin Applications.

Seminars in ophthalmology
PURPOSE: The study explores the evolving landscape of cataract diagnosis, focusing on both traditional methods and innovative technological integrations. It aims to address challenges with subjectivity in traditional cataract grading and to evaluate ...

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.