Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:57.315168Z
Paper Citation Record · LEDGER
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers
As of 17 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2504.15928.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
64 of 64 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 31d01a3e-8e23-4014-a07b-f21b665a37db · outbound
This paper cites an unresolved cited work.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Unresolved cited work
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0d118200-a605-4b03-b329-42f4a68229f4 · outbound
This paper cites The lancet global health commission on global eye health: vision beyond 2020,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers The lancet global health commission on global eye health: vision beyond 2020,
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6bae723f-2f7e-4a76-874d-9618a9363e17 · outbound
This paper cites Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study,
Reference 3
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cba47874-438c-4d95-8439-d4e20c1629b1 · outbound
This paper cites A generalist vision–language foundation model for diverse biomedical tasks,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A generalist vision–language foundation model for diverse biomedical tasks,
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation 1ce81585-a6fd-45b4-bdc0-7b4f6f7e1462 · outbound
This paper cites A deep learning system for detecting diabetic retinopathy across the disease spectrum,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A deep learning system for detecting diabetic retinopathy across the disease spectrum,
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 78ca36b8-2eef-4a0f-9c9f-24fcbd689091 · outbound
This paper cites Automatic staging for retinopathy of prematurity with deep feature fusion and ordinal classification strategy,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Automatic staging for retinopathy of prematurity with deep feature fusion and ordinal classification strategy,
Reference 6
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation efc72dd0-7d60-4b46-80c1-dac4bac3ed41 · outbound
This paper cites A deep network deepopacitynet for detection of cataracts from color fundus photographs,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A deep network deepopacitynet for detection of cataracts from color fundus photographs,
Reference 7
- Resolution
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Source-reported events for the cited work
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Observation 4bb9867b-5109-45ae-a849-5096bb7bbce0 · outbound
This paper cites A foundation model for generalizable disease detection from retinal images,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A foundation model for generalizable disease detection from retinal images,
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 82f8ca3c-5237-44d5-b648-0382310fc7c0 · outbound
This paper cites VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers VisionFM: a Multi-Modal Multi-Task Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f0a5bd23-604f-4ed6-aac3-250ff37f846c · outbound
This paper cites A guide to deep learning in healthcare,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A guide to deep learning in healthcare,
Reference 10
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4a9e1481-20d4-45a6-b9de-c0d48ce0cb3a · outbound
This paper cites On the Opportunities and Risks of Foundation Models.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers On the Opportunities and Risks of Foundation Models
Reference 11
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 50f1fe9f-09e8-4801-b905-91fb6fb4bec9 · outbound
This paper cites On the opportunities and risks of foundation models for natural language processing in radiology,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers On the opportunities and risks of foundation models for natural language processing in radiology,
Reference 12
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 13d6ab5b-15ac-45c5-a8e8-2246a94306a2 · outbound
This paper cites DINOv2: Learning Robust Visual Features without Supervision.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers DINOv2: Learning Robust Visual Features without Supervision
Reference 13
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb51f927-bca8-4576-9caf-cbf58021d051 · outbound
This paper cites Learning transferable visual models from natural language supervision,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Learning transferable visual models from natural language supervision,
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41afe729-c102-445b-9b6d-4c53d017fee5 · outbound
This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Retrieval-augmented generation for knowledge-intensive nlp tasks,
Reference 15
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 53add342-41b8-4fdf-bf38-97778866367a · outbound
This paper cites Query rewriting in retrieval-augmented large language models,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Query rewriting in retrieval-augmented large language models,
Reference 16
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b03d3566-6cae-44d7-8405-85ba38268ba4 · outbound
This paper cites an unresolved cited work.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Unresolved cited work
Reference 17
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 15677ce9-609d-4e92-a473-c6332eddf4cc · outbound
This paper cites User acceptance of information technology: Toward a unified view,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers User acceptance of information technology: Toward a unified view,
Reference 18
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 39248266-4d76-4dde-9ade-45392ea16ead · outbound
This paper cites Visualization of supervised and self-supervised neural networks via attribution guided factorization,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Visualization of supervised and self-supervised neural networks via attribution guided factorization,
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6b9cdb65-6c38-4a86-9715-a998ac6ff8c0 · outbound
This paper cites Code-free deep learning glaucoma detection on color fundus images,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Code-free deep learning glaucoma detection on color fundus images,
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9b257c2d-8fbf-4c8c-ab1c-0b671223782f · outbound
This paper cites Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study,
Reference 21
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 54ca56de-d80d-4bf0-8abb-cf3afb59e13b · outbound
This paper cites Bisonget al., Building machine learning and deep learning models on Google cloud platform.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Bisonget al., Building machine learning and deep learning models on Google cloud platform
Reference 22
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3e1448c7-7425-40b8-96e7-29d71737a4af · outbound
This paper cites Barnes,Microsoft Azure essentials Azure machine learning.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Barnes,Microsoft Azure essentials Azure machine learning
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation dc947805-9a14-4677-9fdf-e34b1bec866d · outbound
This paper cites Towards a general-purpose foundation model for computational pathology,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Towards a general-purpose foundation model for computational pathology,
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b8a58650-208c-4c93-81b5-e1efefba8339 · outbound
This paper cites A visual–language foundation model for pathology image analysis using medical twitter,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers A visual–language foundation model for pathology image analysis using medical twitter,
Reference 25
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e054e2af-ea10-4453-beb3-c2a11b86b2ab · outbound
This paper cites Uncertainty-inspired open set learning for retinal anomaly identification,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Uncertainty-inspired open set learning for retinal anomaly identification,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.848470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 889edc9a-49fc-4fd5-b6c4-7eec1edecad6 · outbound
This paper cites Enhancing ai reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Enhancing ai reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis,
Reference 27
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 35f06673-4ff3-45ab-8773-9407b17291d0 · outbound
This paper cites Deep triplet hashing network for case-based medical image retrieval,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Deep triplet hashing network for case-based medical image retrieval,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.825686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 54bf6c0d-443b-4e05-9946-39cdbb9977dc · outbound
This paper cites Automated assessment of diabetic retinopathy severity using content-based image retrieval in multimodal fundus photographs,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Automated assessment of diabetic retinopathy severity using content-based image retrieval in multimodal fundus photographs,
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation dc31bf5c-e1b5-4474-9cce-eae51bc66859 · outbound
This paper cites Zero-shot text-to-image generation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Zero-shot text-to-image generation,
Reference 30
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2eb192c5-b999-4e6b-841e-0031cc0a47de · outbound
This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Hierarchical Text-Conditional Image Generation with CLIP Latents
Reference 31
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bcebd87-1e2a-4eb7-93cc-e2a223a32d8f · outbound
This paper cites Improving image generation with better captions,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Improving image generation with better captions,
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b585e8c1-0c60-42b0-a64e-47903d374559 · outbound
This paper cites FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generation.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers FundusGAN: A Hierarchical Feature-Aware Generative Framework for High-Fidelity Fundus Image Generation
Reference 33
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d7ea0773-fd81-4993-a1e2-523c5d3ed75e · outbound
This paper cites Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Enhancing Diagnostic Accuracy in Rare and Common Fundus Diseases with a Knowledge-Rich Vision-Language Model
Reference 34
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8cb1216a-0da4-4d44-bbb3-51a936752886 · outbound
This paper cites Cohort profile: the singapore epidemiology of eye diseases study (seed),.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Cohort profile: the singapore epidemiology of eye diseases study (seed),
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e500eb74-611c-4caa-be27-c890532a5b16 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 36
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e45f94b8-11d3-4a4a-871d-54bbb88884a7 · outbound
This paper cites Lora: Low-rank adaptation of large language models.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Lora: Low-rank adaptation of large language models
Reference 37
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9bed1cf4-31c9-42b3-9f1f-185af64a3f9d · outbound
This paper cites Publicly Available Clinical BERT Embeddings.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Publicly Available Clinical BERT Embeddings
Reference 38
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4c3d702-e0fb-451f-b8d7-d80a12e7a428 · outbound
This paper cites What uncertainties do we need in bayesian deep learning for computer vision?.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers What uncertainties do we need in bayesian deep learning for computer vision?
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.762660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c14f360e-225c-4519-994a-5c0627bd61ee · outbound
This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Dropout as a bayesian approximation: Representing model uncertainty in deep learning,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.751460Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bde10eda-e842-4842-b479-5cde2eaa79a6 · outbound
This paper cites Youden index and associated cut-points for three ordinal diagnostic groups,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Youden index and associated cut-points for three ordinal diagnostic groups,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.740809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 64e54255-0935-4f62-952d-4bbca9493b93 · outbound
This paper cites Determining what individual sus scores mean: Adding an adjective rating scale,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Determining what individual sus scores mean: Adding an adjective rating scale,
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.729709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 08b30b7e-3adb-45c6-837b-6073b8b892f6 · outbound
This paper cites Cnns for automatic glaucoma assessment using fundus images: an extensive validation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Cnns for automatic glaucoma assessment using fundus images: an extensive validation,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.718767Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f871f131-bcc8-4462-89c7-7bfef1be86b7 · outbound
This paper cites Deep learning-based glaucoma detection with cropped optic cup and disc and blood vessel segmentation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Deep learning-based glaucoma detection with cropped optic cup and disc and blood vessel segmentation,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.706670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation aa618fcb-dd99-4b7c-9034-1bd2e2eab3fb · outbound
This paper cites Deepdrid: Diabetic retinopathy—grading and image quality estimation challenge,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Deepdrid: Diabetic retinopathy—grading and image quality estimation challenge,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.695120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e71d5523-7d50-43b6-92a0-dcf29120b0d0 · outbound
This paper cites Advancing bag-of-visual-words representations for lesion classification in retinal images,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Advancing bag-of-visual-words representations for lesion classification in retinal images,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.684719Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9a84b146-97ee-40a9-8280-2d511d440e02 · outbound
This paper cites Teleophta: Machine learning and image processing methods for teleophthalmology,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Teleophta: Machine learning and image processing methods for teleophthalmology,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.673534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7f549254-b1d6-4348-b94d-c8ab5f305b3f · outbound
This paper cites Airogs: artificial intelligence for robust glaucoma screening challenge,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Airogs: artificial intelligence for robust glaucoma screening challenge,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.661154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6574dd6f-6ef2-418c-874a-cb901cd0bc2e · outbound
This paper cites Deepopht: medical report generation for retinal images via deep models and visual explanation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Deepopht: medical report generation for retinal images via deep models and visual explanation,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.649776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation fabacc81-cd3f-4a01-bde6-f2ff2413cc84 · outbound
This paper cites Fives: A fundus image dataset for artificial intelligence based vessel segmentation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Fives: A fundus image dataset for artificial intelligence based vessel segmentation,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.637960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 62ed29f7-b8a8-4cea-8ac3-0a95ce195a05 · outbound
This paper cites G1020: A benchmark retinal fundus image dataset for computer-aided glaucoma detection,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers G1020: A benchmark retinal fundus image dataset for computer-aided glaucoma detection,
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.624026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 806b0a44-e43f-4a10-84ca-c4871d291fc4 · outbound
This paper cites Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Image processing based automatic diagnosis of glaucoma using wavelet features of segmented optic disc from fundus image,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.611944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 034325a1-c68e-41ec-b7f4-8d3461fcb4b9 · outbound
This paper cites An adaptive threshold based image processing technique for improved glaucoma detection and classification,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers An adaptive threshold based image processing technique for improved glaucoma detection and classification,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.598877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6ccd35ab-a3d9-4d39-b05b-093be122b19a · outbound
This paper cites Idrid: Diabetic retinopathy–segmentation and grading challenge,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Idrid: Diabetic retinopathy–segmentation and grading challenge,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.586530Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1e7e181e-12df-4da4-b129-d34f289e171a · outbound
This paper cites Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy,
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.573162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7f33795d-b3f1-4816-bc46-808ed0fdad41 · outbound
This paper cites Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Refuge challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs,
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.559182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation febce1d2-b0f5-47e5-b4f1-affe03c3a76b · outbound
This paper cites Origa-light: An online retinal fundus image database for glaucoma analysis and research,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Origa-light: An online retinal fundus image database for glaucoma analysis and research,
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.548574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation c926ff11-bb02-4db6-828d-db1ff4a70ec9 · outbound
This paper cites Dataset from fundus images for the study of diabetic retinopathy,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Dataset from fundus images for the study of diabetic retinopathy,
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.535973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ed1e55f3-6d70-431e-a6f2-8fff0e149b3b · outbound
This paper cites Improving medical images classi- fication with label noise using dual-uncertainty estimation,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Improving medical images classi- fication with label noise using dual-uncertainty estimation,
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.522818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 37fa1ddb-52ad-4e26-a9e4-ccf25797e121 · outbound
This paper cites Auto- matic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Auto- matic detection of 39 fundus diseases and conditions in retinal photographs using deep neural networks,
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.509969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9f9021ca-4ad9-41ad-bb2f-cf7fadc5e6e5 · outbound
This paper cites Retinal fundus multi-disease image dataset (rfmid): A dataset for multi-disease detection research,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Retinal fundus multi-disease image dataset (rfmid): A dataset for multi-disease detection research,
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.498377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 315efc0a-77f6-431a-9dbc-555187b61ed0 · outbound
This paper cites Brset:abrazilian multilabel ophthalmological dataset of retina fundus photos,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Brset:abrazilian multilabel ophthalmological dataset of retina fundus photos,
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.486594Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 013900b8-5de8-4cac-a6e6-3446965cd9b3 · outbound
This paper cites Accuracy assessment of intra- and intervisit fundus image registration for diabetic retinopathy screening,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Accuracy assessment of intra- and intervisit fundus image registration for diabetic retinopathy screening,
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.473955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ca0c5b74-9711-4125-b70c-e591c0aca09c · outbound
This paper cites Identifying medical diagnoses and treatable diseases by image-based deep learning,.
A Clinician-Friendly Platform for Ophthalmic Image Analysis Without Technical Barriers Identifying medical diagnoses and treatable diseases by image-based deep learning,
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-16T11:17:57.459447Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.