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Artificial Intelligence for Pediatric Ophthalmology.
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TLDR
The unique needs of pediatric patients and how artificial intelligence techniques can address these challenges are discussed, recent applications to pediatric ophthalmology are surveyed, and future directions are discussed.Abstract:
PURPOSE OF REVIEW: Despite the impressive results of recent artificial intelligence (AI) applications to general ophthalmology, comparatively less progress has been made toward solving problems in pediatric ophthalmology using similar techniques. This article discusses the unique needs of pediatric ophthalmology patients and how AI techniques can address these challenges, surveys recent applications of AI to pediatric ophthalmology, and discusses future directions in the field.
RECENT FINDINGS: The most significant advances involve the automated detection of retinopathy of prematurity (ROP), yielding results that rival experts. Machine learning (ML) has also been successfully applied to the classification of pediatric cataracts, prediction of post-operative complications following cataract surgery, detection of strabismus and refractive error, prediction of future high myopia, and diagnosis of reading disability via eye tracking. In addition, ML techniques have been used for the study of visual development, vessel segmentation in pediatric fundus images, and ophthalmic image synthesis.
SUMMARY: AI applications could significantly benefit clinical care for pediatric ophthalmology patients by optimizing disease detection and grading, broadening access to care, furthering scientific discovery, and improving clinical efficiency. These methods need to match or surpass physician performance in clinical trials before deployment with patients. Due to widespread use of closed-access data sets and software implementations, it is difficult to directly compare the performance of these approaches, and reproducibility is poor. Open-access data sets and software implementations could alleviate these issues, and encourage further AI applications to pediatric ophthalmology.
KEYWORDS: pediatric ophthalmology, machine learning, artificial intelligence, deep learningread more
Citations
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Journal ArticleDOI
Artificial Intelligence in Retinopathy of Prematurity Diagnosis.
Brittni A. Scruggs,R.V. Paul Chan,Jayashree Kalpathy-Cramer,Michael F. Chiang,J. Peter Campbell +4 more
TL;DR: This review focuses on the development of artificial intelligence for automated diagnosis of plus disease in ROP and highlights the clinical and technical challenges of both the development and implementation of artificial artificial intelligence in the real world.
Journal ArticleDOI
Keratoconus Screening Based on Deep Learning Approach of Corneal Topography.
Bo-I Kuo,Wen-Yi Chang,Tai-Shan Liao,Fang-Yu Liu,Fang-Yu Liu,Hsin-Yu Liu,Hsiao-Sang Chu,Wei-Li Chen,Fung-Rong Hu,Jia-Yush Yen,I-Jong Wang +10 more
TL;DR: The DL models had fair accuracy for keratoconus screening based on corneal topographic images and rendered clinical explainability of deep learning more acceptable, according to ophthalmologists.
Journal ArticleDOI
Automated identification of retinopathy of prematurity by image-based deep learning.
TL;DR: The robust intelligent system developed was able to detect ROP and differentiate four-level classification fundus images with high accuracy and specificity, demonstrating that this system could be used to support clinical decisions.
Journal ArticleDOI
Role of artificial intelligence and machine learning in ophthalmology
John Davis Akkara,Anju Kuriakose +1 more
TL;DR: Artificial intelligence (AI) and machine learning have entered several avenues of modern life, and health care is just one of them, and ophthalmology is a field with a lot of imaging and measurable data, thus ideal for application of AI and ML.
Journal ArticleDOI
Artificial intelligence for retinopathy of prematurity.
TL;DR: The current state of artificial intelligence applications in retinopathy of prematurity (ROP) is reviewed and insight on challenges as well as strategies for bringing these algorithms to the bedside are provided.
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