ReviewCurrent opinion in ophthalmology2020
Artificial intelligence in ophthalmology during COVID-19 and in the post COVID-19 era.
Review in Current opinion in ophthalmology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical image processing and COVID-19: A literature review and bibliometric analysis.Journal of infection and public health · 2022Pooled it
- The Use of Deep Learning in Distinguishing Chalazion and Eyelid Mass.Journal of ophthalmology · 2026Article
- The acceptance of ophthalmic artificial intelligence for eye diseases: a literature review and qualitative analysis.Eye (London, England) · 2025Review
- Robotics and cybersurgery in ophthalmology: a current perspective.Journal of robotic surgery · 2023Review
- Clinical observation of tear film breakup time with a novel smartphone-attachable technology.BMC ophthalmology · 2023Article
- Article
- COVID-19 advising application development for Apple devices (iOS).PeerJ. Computer science · 2023Article
- Planning an artificial intelligence diabetic retinopathy screening program: a human-centered design approach.Frontiers in medicine · 2023Article
- Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care.Current ophthalmology reports · 2023Review
- The Role of Natural Language Processing during the COVID-19 Pandemic: Health Applications, Opportunities, and Challenges.Healthcare (Basel, Switzerland) · 2022Review
- Diabetic Retinopathy and Eye Screening: Diabetic Patients Standpoint, Their Practice, and Barriers; A Cross-Sectional Study.Journal of clinical medicine · 2022Article
- Article
- Applications of natural language processing in ophthalmology: present and future.Frontiers in medicine · 2022Review
- The impact of COVID-19 "Unlock-I" on L V Prasad Eye Institute Network in Southern India.Indian journal of ophthalmology · 2021Article
- Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician.Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)Review
- Usage of artificial intelligence and virtual reality in medical studies.Pakistan journal of medical sciencesArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
purpose of reviewTo highlight artificial intelligence applications in ophthalmology during the COVID-19 pandemic that can be used to: describe ocular findings and changes correlated with COVID-19; extract information from scholarly articles on SARS-CoV-2 and COVID-19 specific to ophthalmology; and implement efficient patient triage and telemedicine care. RECENT
findingsOphthalmology has been leading in artificial intelligence and technology applications. With medical imaging analysis, pixel-annotated distinguishable features on COVID-19 patients may help with noninvasive diagnosis and severity outcome predictions. Using natural language processing (NLP) and data integration methods, topic modeling on more than 200 ophthalmology-related articles on COVID-19 can summarize ocular manifestations, viral transmission, treatment strategies, and patient care and practice management. Artificial intelligence for telemedicine applications can address the high demand, prioritize and triage patients, as well as improve at home-monitoring devices and secure data transfers. SUMMARY: COVID-19 is significantly impacting the way we are delivering healthcare. Given the already successful implementation of artificial intelligence applications and telemedicine in ophthalmology, we expect that these systems will be embraced more as tools for research, education, and patient care.
Indexed as
Identifiers
What OpenQuestion holds
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.