AIMC Topic: Vision Disorders

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Fusion of deep transfer learning models with Gannet optimisation algorithm for an advanced image captioning system for visual disabilities.

Scientific reports
The issue of generating a natural language explanation of images to define their visual content has garnered significant attention in computer vision (CV) and natural language processing (NLP). It is driven by applications such as image virtual assis...

An innovative multi-head attention mechanism-driven recurrent neural network model with feature representation fusion for enhanced image captioning to assist individuals with visual impairments.

Scientific reports
Developments in image captioning technologies played a crucial role in improving the quality of life for individuals with visual impairments, advancing better social inclusivity. Image captioning is the task of representing the visual content of the ...

The efficiency of sensory systems in postural control of children with and without hearing or visual impairments.

PloS one
Limited evidence exists on the efficiency of the sensory systems of children with sensory impairment. The purpose of this study was to examine the sensory systems involved in postural control of male children with hearing (HI) or visual impairments (...

Developmental coordination disorder and cerebral visual impairment: What is the association?

Research in developmental disabilities
INTRODUCTION: Children with Developmental Coordination Disorder (DCD) experience impairments beyond motor planning, affecting visual perceptual and visual-motor integration abilities, similar to children with Cerebral Visual Impairment (CVI), making ...

SMOTE-Enhanced Explainable Artificial Intelligence Model for Predicting Visual Field Progression in Myopic Normal Tension Glaucoma.

Journal of glaucoma
PRCIS: The AI model, enhanced by SMOTE to balance data classes, accurately predicted visual field deterioration in patients with myopic normal tension glaucoma. Using SHAP analysis, the key variables driving disease progression were identified.

A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.

Frontiers in endocrinology
OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after su...

Identifying Factors Associated With Fast Visual Field Progression in Patients With Ocular Hypertension Based on Unsupervised Machine Learning.

Journal of glaucoma
PRCIS: We developed unsupervised machine learning models to identify different subtypes of patients with ocular hypertension in terms of visual field (VF) progression and discovered 4 subtypes with different trends of VF worsening. We then identified...

Prediction of visual field progression with serial optic disc photographs using deep learning.

The British journal of ophthalmology
AIM: We tested the hypothesis that visual field (VF) progression can be predicted with a deep learning model based on longitudinal pairs of optic disc photographs (ODP) acquired at earlier time points during follow-up.