ArticleScientific data2022
PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed, 110 citations in OpenAlex.
- Learning Ophthalmologist Clinical Reasoning for Glaucoma Diagnosis from Fundus Images.medRxiv : the preprint server for health sciences · 2026Article
- Automated Optic Disc Tilt Classification in Fundus Photographs Using Segmentation and the Elliptical Ratio: External Clinical Validation Study.JMIR formative research · 2026Article
- Fundus to fluorescein angiography video generation as a retinal generative foundation model.NPJ digital medicine · 2026Article
- Retinal lesion annotation on fundus imaging: an interobserver variability study.Scientific reports · 2026Article
- AUBADE-syn: a novel deep learning ensemble method for glaucoma detection using synthetic fundus images on imbalanced datasets.NPJ digital medicine · 2026Article
- Boosting foundation models for rare eye disease diagnosis via a multimodal text-to-image generative framework.NPJ digital medicine · 2026Article
- Uncertainty-Aware Training for Ophthalmic Segmentation Using MedSAM.Translational vision science & technology · 2026Article
- Classifying retinal images via vascular-optic disc cross-segmentation and attentive feature selection.Scientific reports · 2026Article
- Can a Natural Image-Based Foundation Model Outperform a Retina-Specific Model in Detecting Ocular and Systemic Diseases?Ophthalmology science · 2026Article
- Compact vision models match domain-specific foundation models for several retinal imaging classification tasks: A systematic benchmark.PloS one · 2026Article
- Benchmarking Vision Encoders for Image Classification in Ophthalmology.Computational and structural biotechnology journal · 2026Article
- VascX Models: Deep Ensembles for Retinal Vascular Analysis From Color Fundus Images.Translational vision science & technology · 2025Article
- A multimodal visual-language foundation model for computational ophthalmology.NPJ digital medicine · 2025Article
- A narrative review of foundation models for medical image segmentation: zero-shot performance evaluation on diverse modalities.Quantitative imaging in medicine and surgery · 2025Review
- Optic Cup and Disc Segmentation of Fundus Images Using Artificial Intelligence Externally Validated With Optical Coherence Tomography Measurements.Translational vision science & technology · 2025Article
- FOVEA: Preoperative and intraoperative retinal fundus images with optic disc and retinal vessel annotations.Scientific data · 2025Article
- FairDiffusion: Enhancing equity in latent diffusion models via fair Bayesian perturbation.Science advances · 2025Article
- A data-efficient strategy for building high-performing medical foundation models.Nature biomedical engineering · 2025Article
- The Boundaries of Fair AI in Medical Image Prognosis: A Causal Perspective.Advances in neural information processing systems · 2025Article
- Narrative Review of Artificial Intelligence in Ophthalmic Disease Detection : Artificial Intelligence in Ophthalmic Diseases Detection.Galen medical journal · 2025Review
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Glaucoma is one of the ophthalmological diseases that frequently causes loss of vision in today's society. Previous studies assess which anatomical parameters of the optic nerve can be predictive of glaucomatous damage, but to date there is no test that by itself has sufficient sensitivity and specificity to diagnose this disease. This work provides a public dataset with medical data and fundus images of both eyes of the same patient. Segmentations of the cup and optic disc, as well as the labeling of the patients based on the evaluation of clinical data are also provided. The dataset has been tested with a neural network to classify healthy and glaucoma patients. Specifically, the ResNet-50 has been used as the basis to classify patients using information from each eye independently as well as using the joint information from both eyes of each patient. Results provide the baseline metrics, with the aim of promoting research in the early detection of glaucoma based on the joint analysis of both eyes of the same patient.
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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.