AIMC Topic: Ophthalmologists

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Grader Variability and the Importance of Reference Standards for Evaluating Machine Learning Models for Diabetic Retinopathy.

Ophthalmology Mar 13, 2018
PURPOSE: Use adjudication to quantify errors in diabetic retinopathy (DR) grading based on individual graders and majority decision, and to train an improved automated algorithm for DR grading.
Middle Aged Humans Reference Standards Ophthalmologists Diabetic Retinopathy Clinical Competence Retrospective Studies Machine Learning ROC Curve Female Algorithms Mass Screening Male
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Automated Identification of Diabetic Retinopathy Using Deep Learning.

Ophthalmology Mar 27, 2017
PURPOSE: Diabetic retinopathy (DR) is one of the leading causes of preventable blindness globally. Performing retinal screening examinations on all diabetic patients is an unmet need, and there are many undiagnosed and untreated cases of DR. The obje...
Image Interpretation, Computer-Assisted Machine Learning Diagnostic Techniques, Ophthalmological Humans Algorithms Ophthalmologists Diabetic Retinopathy Reproducibility of Results Neural Networks, Computer ROC Curve
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Deep learning-based automatic differentiation of acute angle closure with or without zonulopathy using ultrasound biomicroscopy: a comparison of diagnostic performance with ophthalmologists.

BMJ open ophthalmology May 22, 2025
OBJECTIVE: This study aims to develop ultrasound biomicroscopy (UBM)-based artificial intelligence (AI) models for preoperative differentiation of acute angle closure (AAC) with or without zonulopathy and to compare their comprehensive diagnostic per...
Ophthalmologists Glaucoma, Angle-Closure Deep Learning Aged Humans ROC Curve Cross-Sectional Studies Female Tomography, Optical Coherence Diagnosis, Differential Male Acute Disease Middle Aged Ligaments Microscopy, Acoustic
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Evaluation of AI Summaries on Interdisciplinary Understanding of Ophthalmology Notes.

JAMA ophthalmology May 1, 2025
IMPORTANCE: Specialized ophthalmology terminology limits comprehension for nonophthalmology clinicians and professionals, hindering interdisciplinary communication and patient care. The clinical implementation of large language models (LLMs) into pra...
Artificial Intelligence Electronic Health Records Female Adult Humans Quality Improvement Comprehension Interdisciplinary Communication Ophthalmologists Male Middle Aged Surveys and Questionnaires Ophthalmology
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An Open-Source Deep Learning Algorithm for Efficient and Fully Automatic Analysis of the Choroid in Optical Coherence Tomography.

Translational vision science & technology Nov 1, 2023
PURPOSE: To develop an open-source, fully automatic deep learning algorithm, DeepGPET, for choroid region segmentation in optical coherence tomography (OCT) data.
Algorithms Deep Learning Choroid Tomography, Optical Coherence Humans Ophthalmologists
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Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study.

The Lancet. Digital health Aug 1, 2021
BACKGROUND: Medical artificial intelligence (AI) has entered the clinical implementation phase, although real-world performance of deep-learning systems (DLSs) for screening fundus disease remains unsatisfactory. Our study aimed to train a clinically...
Retina Expert Systems Retinal Diseases Biomedical Technology Area Under Curve Fundus Oculi Models, Biological Photography Ophthalmologists Diabetic Retinopathy Artificial Intelligence Deep Learning China ROC Curve Image Processing, Computer-Assisted Mass Screening Humans
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Interpretation of artificial intelligence studies for the ophthalmologist.

Current opinion in ophthalmology Sep 1, 2020
PURPOSE OF REVIEW: The use of artificial intelligence (AI) in ophthalmology has increased dramatically. However, interpretation of these studies can be a daunting prospect for the ophthalmologist without a background in computer or data science. This...
Humans Artificial Intelligence Delivery of Health Care Data Interpretation, Statistical Ophthalmology Ophthalmologists
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Fundamentals of artificial intelligence for ophthalmologists.

Current opinion in ophthalmology Sep 1, 2020
PURPOSE OF REVIEW: As artificial intelligence continues to develop new applications in ophthalmic image recognition, we provide here an introduction for ophthalmologists and a primer on the mechanisms of deep learning systems.
Image Interpretation, Computer-Assisted Eye Diseases Ophthalmologists Neural Networks, Computer Deep Learning Diagnostic Imaging Humans
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Workforce Shortage for Retinopathy of Prematurity Care and Emerging Role of Telehealth and Artificial Intelligence.

Pediatric clinics of North America Aug 1, 2020
Retinopathy of prematurity (ROP) is the leading cause of childhood blindness in very-low-birthweight and very preterm infants in the United States. With improved survival of smaller babies, more infants are at risk for ROP, yet there is an increasing...
Neonatal Screening Retinopathy of Prematurity Ophthalmologists Intensive Care Units, Neonatal United States Telemedicine Artificial Intelligence Infant, Premature Infant, Newborn Humans Infant Surveys and Questionnaires
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ASSESSMENT OF CENTRAL SEROUS CHORIORETINOPATHY DEPICTED ON COLOR FUNDUS PHOTOGRAPHS USING DEEP LEARNING.

Retina (Philadelphia, Pa.) Aug 1, 2020
PURPOSE: To investigate whether and to what extent central serous chorioretinopathy (CSC) depicted on color fundus photographs can be assessed using deep learning technology.
Humans Female Adult Male Middle Aged Diagnosis, Computer-Assisted Deep Learning Fundus Oculi Photography ROC Curve Ophthalmologists Area Under Curve Central Serous Chorioretinopathy Tomography, Optical Coherence
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