AIMC Topic: Strabismus

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Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study.

JMIR formative research
BACKGROUND: Strabismus measurement is essential in vision assessment and screening. It typically requires skilled clinicians or specialized equipment. Photographic strabismus measurement methods have value in terms of accessibility and convenience of...

StrabNet-CQ: an integrated deep learning framework for automated strabismus classification and quantification using ocular landmark detection.

BMC ophthalmology
BACKGROUND: Strabismus is a common ocular misalignment that can impair binocular vision if untreated. Conventional diagnosis and treatment rely on clinical prism diopter (PD) readings, which quantify deviation along with base direction. However, thes...

Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.

Journal of medical Internet research
BACKGROUND: Traditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting artificial intelligence (AI) model development and clinical application.

Advancements in strabismus diagnosis: A comprehensive systematic review of artificial intelligence and digital health applications.

Experimental eye research
PURPOSE: To review the accuracy of artificial intelligence (AI) and digital health applications in the screening and diagnosis of strabismus.

Accuracy and Readability of ChatGPT Responses to Patient-Centric Strabismus Questions.

Journal of pediatric ophthalmology and strabismus
PURPOSE: To assess the medical accuracy and readability of responses provided by ChatGPT (OpenAI), the most widely used artificial intelligence-powered chatbot, regarding questions about strabismus.

High-Accuracy Intermittent Strabismus Screening via Wearable Eye-Tracking and AI-Enhanced Ocular Feature Analysis.

Biosensors
An effective and highly accurate strabismus screening method is expected to identify potential patients and provide timely treatment to prevent further deterioration, such as amblyopia and even permanent vision loss. To satisfy this need, this work s...

Automated strabismus detection and classification using deep learning analysis of facial images.

Scientific reports
Strabismus, or eye misalignment, is a common condition affecting individuals of all ages. Early detection and accurate classification are essential for proper treatment and avoiding long-term complications. This research presents a new deep-learning-...

Integrating artificial intelligence in strabismus management: current research landscape and future directions.

Experimental biology and medicine (Maywood, N.J.)
Advancements in artificial intelligence (AI) are transforming strabismus management through improved screening, diagnosis, and surgical planning. Deep learning has notably enhanced diagnostic accuracy and optimized surgical outcomes. Despite these ad...

Chatbots talk Strabismus: Can AI become the new patient Educator?

International journal of medical informatics
BACKGROUND: Strabismus is a common eye condition affecting both children and adults. Effective patient education is crucial for informed decision-making, but traditional methods often lack accessibility and engagement. Chatbots powered by AI have eme...

Artificial Intelligence for Early Detection of Pediatric Eye Diseases Using Mobile Photos.

JAMA network open
IMPORTANCE: Identifying pediatric eye diseases at an early stage is a worldwide issue. Traditional screening procedures depend on hospitals and ophthalmologists, which are expensive and time-consuming. Using artificial intelligence (AI) to assess chi...