ArticleData in brief2023
Dataset of fundus images for the diagnosis of ocular toxoplasmosis.
Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
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.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Clinical and imaging characterization of ocular toxoplasmosis in a Central-West Brazilian population.International ophthalmology · 2026Article
- An explainable biomedical foundation model via large-scale concept-enhanced vision-language pretraining.Nature biomedical engineering · 2026Article
- A test-time clinically adaptive framework for detecting multiple fundus diseases harnessing ophthalmic foundation models.NPJ digital medicine · 2026Article
- A Systematic Review and Meta-Analysis of Diagnostic Test Accuracy for Human Toxoplasmosis: Performance, Populations, and Validation Gaps.Medical devices (Auckland, N.Z.) · 2026Review
- Interpretable multi-model deep learning framework for automated four-class diagnosis of ocular toxoplasmosis using fundus imaging.Scientific reports · 2025Article
- The Evolution of Artificial Intelligence in Ocular Toxoplasmosis Detection: A Scoping Review on Diagnostic Models, Data Challenges, and Future Directions.Infectious disease reports · 2025Review
Corrections and comments
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Authors and funding
13 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Toxoplasmosis chorioretinitis is commonly diagnosed by an ophthalmologist through the evaluation of the fundus images of a patient. Early detection of these lesions may help to prevent blindness. In this article we present a data set of fundus images labeled into three categories: healthy eye, inactive and active chorioretinitis. The dataset was developed by three ophthalmologists with expertise in toxoplasmosis detection using fundus images. The dataset will be of great use to researchers working on ophthalmic image analysis using artificial intelligence techniques for the automatic detection of toxoplasmosis chorioretinitis.
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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.