ReviewCurrent opinion in ophthalmology2022
Towards effective data sharing in ophthalmology: data standardization and data privacy.
Review in Current opinion in ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
- Review
- Optimal machine learning models and factors for global infectious diseases: An ecological analysis.Infectious medicine · 2026Article
- AI-driven virtual cell models in preclinical research: technical pathways, validation mechanisms, and clinical translation potential.NPJ digital medicine · 2025Review
- Attitudes Toward Common Data Models Among Chinese Biomedical Professionals: Cross-Sectional Survey.JMIR medical informatics · 2025Article
- Current status and solutions for AI ethics in ophthalmology: a bibliometric analysis.NPJ digital medicine · 2025Article
- Gap Analysis of Standard Automated Perimetry Concept Representation in Medical Terminologies.Journal of glaucoma · 2025Article
- The march to harmonized imaging standards for retinal imaging.Progress in retinal and eye research · 2025Review
- Artificial intelligence, data sharing, and privacy for retinal imaging under Brazilian Data Protection Law.International journal of retina and vitreous · 2025Article
- Exploring Publicly Accessible Optical Coherence Tomography Datasets: A Comprehensive Overview.Diagnostics (Basel, Switzerland) · 2024Review
- Concept Coverage Analysis of Ophthalmic Infections and Trauma among the Standardized Medical Terminologies SNOMED-CT, ICD-10-CM, and ICD-11.Ophthalmology science · 2023Article
- Advancing Toward a Common Data Model in Ophthalmology: Gap Analysis of General Eye Examination Concepts to Standard Observational Medical Outcomes Partnership (OMOP) Concepts.Ophthalmology science · 2023Article
- A multi-object deep neural network architecture to detect prostate anatomy in T2-weighted MRI: Performance evaluation.Frontiers in nuclear medicine · 2022Article
- Gap Analysis of Glaucoma Examination Concept Representations within Standard Systemized Nomenclature of Medicine - Clinical Terms.Ophthalmology. GlaucomaArticle
- Variations in Electronic Health Record-Based Definitions of Diabetic Retinopathy Cohorts: A Literature Review and Quantitative Analysis.Ophthalmology scienceArticle
- Federated Learning in Glaucoma: A Comprehensive Review and Future Perspectives.Ophthalmology. GlaucomaReview
- Implementing a Common Data Model in Ophthalmology: Mapping Structured Electronic Health Record Ophthalmic Examination Data to Standard Vocabularies.Ophthalmology scienceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
purpose of reviewThe purpose of this review is to provide an overview of updates in data standardization and data privacy in ophthalmology. These topics represent two key aspects of medical information sharing and are important knowledge areas given trends in data-driven healthcare. RECENT
findingsStandardization and privacy can be seen as complementary aspects that pertain to data sharing. Standardization promotes the ease and efficacy through which data is shared. Privacy considerations ensure that data sharing is appropriate and sufficiently controlled. There is active development in both areas, including government regulations and common data models to advance standardization, and application of technologies such as blockchain and synthetic data to help tackle privacy issues. These advancements have seen use in ophthalmology, but there are areas where further work is required. SUMMARY: Information sharing is fundamental to both research and care delivery, and standardization/privacy are key constituent considerations. Therefore, widespread engagement with, and development of, data standardization and privacy ecosystems stand to offer great benefit to ophthalmology.
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.