AIMC Topic: Eye

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Using explainable machine learning to predict the irritation and corrosivity of chemicals on eyes and skin.

Toxicology letters
Contact with specific chemicals often results in corrosive and irritative responses in the eyes and skin, playing a pivotal role in assessing the potential hazards of personal care products, cosmetics, and industrial chemicals to human health. While ...

Detection of Systemic Diseases From Ocular Images Using Artificial Intelligence: A Systematic Review.

Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
PURPOSE: Despite the huge investment in health care, there is still a lack of precise and easily accessible screening systems. With proven associations to many systemic diseases, the eye could potentially provide a credible perspective as a novel scr...

[Construction of an interpretable machine learning-based prediction model for the clinical effect on ischemic stroke in treatment with eye acupuncture combined with rehabilitation therapy].

Zhongguo zhen jiu = Chinese acupuncture & moxibustion
OBJECTIVE: To construct a prediction model for the clinical effect of eye acupuncture combined with rehabilitation therapy on ischemic stroke based on interpretable machine learning.

Visual analysis of autoimmune dry eye studies based on bibliometrics.

Medicine
BACKGROUND: Dry eye is a chronic ocular surface disease caused by the instability of tear film or the imbalance of the ocular surface microenvironment which can lead to a diverse range of ocular discomfort symptoms. At present, the relevant mechanism...

Prediction of Central Visual Field Measures From Macular OCT Volume Scans With Deep Learning.

Translational vision science & technology
PURPOSE: Predict central 10° global and local visual field (VF) measurements from macular optical coherence tomography (OCT) volume scans with deep learning (DL).

Evaluation and Comparison of Ophthalmic Scientific Abstracts and References by Current Artificial Intelligence Chatbots.

JAMA ophthalmology
IMPORTANCE: Language-learning model-based artificial intelligence (AI) chatbots are growing in popularity and have significant implications for both patient education and academia. Drawbacks of using AI chatbots in generating scientific abstracts and...