AI Medical Compendium Topic

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Diagnostic Techniques, Ophthalmological

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Advances in artificial intelligence for meibomian gland evaluation: A comprehensive review.

Survey of ophthalmology
Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to evaporative dry eye, significantly impacting visual quality. With a global prevalence estimated at 35.8 %, it presents substantial challenges for clinicians. Co...

Applications of Artificial Intelligence in Diagnosis of Dry Eye Disease: A Systematic Review and Meta-Analysis.

Cornea
PURPOSE: Clinical diagnosis of dry eye disease is based on a subjective Ocular Surface Disease Index questionnaire or various objective tests, however, these diagnostic methods have several limitations.

Artificial intelligence in ophthalmology.

Current opinion in ophthalmology
PURPOSE OF REVIEW: To review role of artificial intelligence in medicine.

Applications of artificial intelligence to inherited retinal diseases: A systematic review.

Survey of ophthalmology
Artificial intelligence(AI)-based methods have been extensively used for the detection and management of various common retinal conditions, but their targeted development for inherited retinal diseases (IRD) is still nascent. In the context of limite...

Smartphone pupillometry with machine learning differentiates ischemic from hemorrhagic stroke: A pilot study.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
OBJECTIVES: Similarities between acute ischemic and hemorrhagic stroke make diagnosis and triage challenging. We studied a smartphone-based quantitative pupillometer for differentiation of acute ischemic and hemorrhagic stroke.

Internal validation of a convolutional neural network pipeline for assessing meibomian gland structure from meibography.

Optometry and vision science : official publication of the American Academy of Optometry
SIGNIFICANCE: Optimal meibography utilization and interpretation are hindered due to poor lid presentation, blurry images, or image artifacts and the challenges of applying clinical grading scales. These results, using the largest image dataset analy...

Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

JAMA network open
IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of thes...

AI for Corneal Imaging: How Will This Help Us Take Care of Our Patients?

Cornea
As artificial intelligence continues to evolve at a rapid pace, there is growing enthusiasm surrounding the potential for novel applications in corneal imaging. This article provides an overview of the potential for such applications, as well as the ...

Application of Artificial Intelligence in the Diagnosis, Follow-Up and Prediction of Treatment of Ophthalmic Diseases.

Seminars in ophthalmology
PURPOSE: To describe the application of artificial intelligence (AI) in ophthalmic diseases and its possible future directions.