ReviewFrontiers in medicine2021
The Impact of Artificial Intelligence and Deep Learning in Eye Diseases: A Review.
Review in Frontiers in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
18 citing papers in PubMed.
- A scoping review of advancements in machine learning for glaucoma: current trends and future direction.Frontiers in medicine · 2025Article
- Deep learning models for tendinopathy detection: a systematic review and meta-analysis of diagnostic tests.EFORT open reviews · 2024Article
- Predicting an opaque bubble layer during small-incision lenticule extraction surgery based on deep learning.Frontiers in cell and developmental biology · 2024Article
- Deep learning-based diagnosis of disease activity in patients with Graves' orbitopathy using orbital SPECT/CT.European journal of nuclear medicine and molecular imaging · 2023Article
- A Radiomic-Based Machine Learning System to Diagnose Age-Related Macular Degeneration from Ultra-Widefield Fundus Retinography.Diagnostics (Basel, Switzerland) · 2023Article
- Deep learning in precision medicine and focus on glioma.Bioengineering & translational medicine · 2023Review
- Review
- Evaluating the Efficacy of Teleophthalmology in Delivering Ophthalmic Care to Underserved Populations: A Literature Review.Journal of clinical medicine · 2023Review
- Precision Medicine in Glaucoma: Artificial Intelligence, Biomarkers, Genetics and Redox State.International journal of molecular sciences · 2023Review
- Research progress in artificial intelligence assisted diabetic retinopathy diagnosis.International journal of ophthalmology · 2023Article
- Advances in artificial intelligence models and algorithms in the field of optometry.Frontiers in cell and developmental biology · 2023Review
- A Prediction Model for Sight-Threatening Diabetic Retinopathy Based on Plasma Adipokines among Patients with Mild Diabetic Retinopathy.Journal of diabetes research · 2023Article
- Optical coherence tomography image based eye disease detection using deep convolutional neural network.Health information science and systems · 2022Article
- Artificial intelligence and corneal diseases.Current opinion in ophthalmology · 2022Review
- Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.Journal of the Association for Research in Otolaryngology : JARO · 2022Review
- Review of Machine Learning Applications Using Retinal Fundus Images.Diagnostics (Basel, Switzerland) · 2022Review
- The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques.Frontiers in medicine · 2022Review
- Review for special issue: Corneal lamellar surgery: Present outcomes and future perspectives.Taiwan journal of ophthalmologyReview
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is a subset of computer science dealing with the development and training of algorithms that try to replicate human intelligence. We report a clinical overview of the basic principles of AI that are fundamental to appreciating its application to ophthalmology practice. Here, we review the most common eye diseases, focusing on some of the potential challenges and limitations emerging with the development and application of this new technology into ophthalmology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.