Topics and Trends in Most Cited Retinal Diseases and Treatments Papers, Class of 2026

What topics and trends defined most-cited Retinal Diseases and Treatments research in the Class of 2026?

Diabetic retinopathy, anti-VEGF therapy, AMD, and diabetic macular edema define the Class of 2026 retinal cohort, with fundus imaging and OCT still prominent alongside inherited retinal degeneration and DR screening. DME, DR screening, and inherited disease rose sharply from Class of 2025, while CNN-based classification and standalone fundus-imaging studies receded among top-cited papers.

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Updated July 13, 2026

At a glance

Field: Retinal Diseases and Treatments
Cohort label: Class of 2026 (2024 publications)
Papers analyzed: 7,789
Papers ranked: 20
Top topics in ranked papers: Diabetic retinopathy, Anti-VEGF therapy, Age-related macular degeneration, Diabetic macular edema, Fundus image
Publication window: Jan 1, 2024 – Dec 31, 2024
Eligibility: Research articles; reviews excluded
Citation window: 18 months post-publication
18m citation range: 43–153
Data source: OpenAlex · Retrieved Jul 2026
License: CC BY 4.0

Rankings

20 papers ranked by 18-month citation count

#1 of 7,789

15318m citations

Integrated image-based deep learning and language models for primary diabetes care

Jiajia Li, Zhouyu Guan, Jing Wang et al.Nature Medicine202410.1038/s41591-024-03139-8

CorrespondingLi Jia Chen, Weiping Jia, Yih Chung Tham, Huating Li, Bin Sheng, Tien Yin WongInstitutionShanghai Jiao Tong University, China

DeepDR-LLMDeepDR-TransformerDiabetic retinopathy screeningDeep learning-based image classificationlarge language modelprimary care physiciansindividualized diabetes management recommendationsAI diagnostic accuracydiabetes self-management adherenceDR referral adherenceReal-world evidenceRetrospective studyEnglish-Chinese language performance comparisonendocrinology residents benchmarklow-resource setting healthcareempathy in clinical recommendationsnewly diagnosed diabetes patientsdigital health solutionhuman-AI collaboration in healthcare

#2 of 7,789

15018m citations

A deep learning system for predicting time to progression of diabetic retinopathy

Ling Dai, Bin Sheng, Tingli Chen, Qiang Wu, Ruhan Liu, Huating Li et al.Nature Medicine202410.1038/s41591-023-02702-z

CorrespondingBin Sheng, Huating Li, Tien Yin Wong, Weiping JiaInstitutionShanghai Jiao Tong University, China

DeepDR PlusDeep learningDiabetic retinopathy predictionFundus imagetime-to-event predictionconcordance indexintegrated Brier scoreScreening interval extensionmultiethnic datasetmodel pretrainingDiabetic retinopathyReal-world evidenceRisk stratificationsurvival analysis in ophthalmologydelayed detection ratediabetes screening workflow integrationindividualized risk prediction

#3 of 7,789

11818m citations

Gene Editing for <i>CEP290</i> -Associated Retinal Degeneration

Eric A Pierce et al.New England Journal of Medicine202410.1056/nejmoa2309915

CorrespondingEric A PierceInstitutionFrom the Ocular Genomics Institute, United States

EDIT-101CEP290 IVS26 variantCRISPR-Cas9 gene editingin vivo gene editingSubretinal injectionLeber congenital amaurosisInherited retinal degenerationfull-field stimulus testingBest-corrected visual acuity (BCVA)Ora-Visual Navigation Challenge mobility testNational Eye Institute Visual Function Questionnaire-25Children's Visual Function QuestionnairePhotoreceptorsdose-limiting toxicity assessmentphotoreceptor gene therapyBRILLIANCE clinical trial

#4 of 7,789

11618m citations

Intravitreal aflibercept 8 mg in neovascular age-related macular degeneration (PULSAR): 48-week results from a randomised, double-masked, non-inferiority, phase 3 trial

Paolo Lanzetta et al.The Lancet202410.1016/s0140-6736(24)00063-1

CorrespondingJeffrey S. HeierInstitutionUniversity of Udine, Italy

AfliberceptNeovascular age-related macular degenerationPULSAR trialNoninferiority trial designExtended dosing intervalAnti-VEGF therapyBest-corrected visual acuity (BCVA)Intraretinal fluid resolution

#5 of 7,789

8418m citations

Improved Support Vector Machine based on CNN-SVD for vision-threatening diabetic retinopathy detection and classification

Anas Bilal et al.PLoS ONE202410.1371/journal.pone.0295951

CorrespondingAnas Bilal, Azhar Imran, Talha Imtiaz Baig, Xiaowen Liu, Haixia Long, Abdulkareem Alzahrani, Muhammad ShafiqInstitutionHainan Normal University, China

Diabetic retinopathyHierarchical Block Attention (HBA)HBA-U-NetHybrid deep learning modelImproved Support Vector Machine-Radial Basis Function (ISVM-RBF)attention mechanism in image segmentationFundus imageDiabetic retinopathy classificationIDRiD datasetChannel-wise attention mechanismspatial attentionFeature extractionDecision Tree classifierk-nearest neighbors classifierImage preprocessingDiabetic retinopathy diagnosismulti-stage classification strategyOphthalmic disease diagnosis

#6 of 7,789

7318m citations

OCTA-500: A retinal dataset for optical coherence tomography angiography study

Mingchao Li et al.Medical Image Analysis202410.1016/j.media.2024.103092

CorrespondingSongtao Yuan, Qiang ChenInstitutionNanjing University of Science and Technology, China

OCTA-500Optical coherence tomography angiographyRetinal image datasetRetinal imagingImage segmentationfoveal avascular zoneRetinal vasculatureImage quality assessmentprojection artifactsdeep learning benchmarkingDiabetic retinopathy diagnosisquantitative biomarkers

#7 of 7,789

7118m citations

TENAYA and LUCERNE

Arshad M Khanani et al.Ophthalmology202410.1016/j.ophtha.2024.02.014

CorrespondingArshad M. KhananiInstitutionUniversity of Nevada, Reno, United States

FaricimabAngiopoietin-2 inhibitionAnti-VEGF therapyNeovascular age-related macular degenerationAfliberceptIntravitreal injectionTreat-and-extend regimenEvery-16-week dosingQ12W dosingQ8W dosingBest-corrected visual acuity (BCVA)Noninferiority trial designTreatment-naïveExtended dosing intervalocular adverse eventsTENAYA trialLUCERNE trialdisease activity-based dosingDurability of treatment effect

#8 of 7,789

7018m citations

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods

Mikhail Kulyabin et al.Scientific Data202410.1038/s41597-024-03182-7

CorrespondingMikhail KulyabinInstitutionFriedrich-Alexander-Universität Erlangen-Nürnberg, Germany

Optical coherence tomographyOCTDL datasetRetinal imagingAge-related macular degenerationDiabetic macular edemaEpiretinal Membrane (ERM)Retinal artery occlusionRetinal vein occlusionVitreomacular Interface Disease (VID)Optovue Avanti RTVue XR deviceraster scanning protocolDeep learning-based image classificationopen-access medical imaging datasetretinal pathology labelinglight wave interference imagingOphthalmic disease diagnosis

#9 of 7,789

7018m citations

Global burden of low vision and blindness due to age-related macular degeneration from 1990 to 2021 and projections for 2050

Shiyan Zhang et al.BMC Public Health202410.1186/s12889-024-21047-x

CorrespondingJianping RenInstitutionHangzhou Normal University, China

Age-related macular degenerationGlobal Burden of Disease (GBD 2021) studyDisability-adjusted life years (DALYs)Age-standardized prevalence rate (ASPR)Age-standardized DALY rate (ASDALYR)Estimated annual percentage change (EAPC)K-means clusteringAutoregressive Integrated Moving Average (ARIMA) modelExponential Smoothing (ES) modelSocio-Demographic Index (SDI)Low visionblindnessSub-Saharan Africa regional trendsSex-based disease burden disparityAge-related disease burdenPopulation aging2050 burden projectionsRegional stratification by socioeconomic development204 countries and regions coveragePublic health resource allocation

#10 of 7,789

6418m citations

Phenotyping and genotyping inherited retinal diseases: Molecular genetics, clinical and imaging features, and therapeutics of macular dystrophies, cone and cone-rod dystrophies, rod-cone dystrophies, Leber congenital amaurosis, and cone dysfunction syndromes

Michalis Georgiou et al.Progress in Retinal and Eye Research202410.1016/j.preteyeres.2024.101244

CorrespondingMichel MichaelidesInstitutionMoorfields Eye Hospital, United Kingdom

macular dystrophiescone dystrophiescone-rod dystrophiesrod-cone dystrophiesLeber congenital amaurosiscone dysfunction syndromesInherited retinal degenerationgenotype-phenotype correlationRetinal imaginggene therapy for retinal diseaseOptical coherence tomographyFundus autofluorescence imagingElectroretinographynext-generation sequencingStargardt diseaseABCA4 geneRPE65 geneachromatopsia

#11 of 7,789

6018m citations

Oral Antioxidant and Lutein/Zeaxanthin Supplements Slow Geographic Atrophy Progression to the Fovea in Age-Related Macular Degeneration

Tiarnán D L Keenan et al.Ophthalmology202410.1016/j.ophtha.2024.07.014

CorrespondingTiarnán D L KeenanInstitutionNational Institutes of Health, United States

Geographic atrophyAge-related macular degenerationoral antioxidant supplementsluteinzeaxanthinfoveaprogression ratemacular pigmentAREDS formulationFundus autofluorescence imagingcentral vision preservationcarotenoid supplementationRetinal pigment epithelium

#12 of 7,789

5818m citations

Gene therapy for neovascular age-related macular degeneration by subretinal delivery of RGX-314: a phase 1/2a dose-escalation study

Peter A Campochiaro et al.The Lancet202410.1016/s0140-6736(24)00310-6

CorrespondingPeter A. CampochiaroInstitutionJohns Hopkins University, United States

RGX-314Neovascular age-related macular degenerationSubretinal injectionGene therapydose-escalation studyAdeno-associated virus (AAV) vectorAnti-VEGF therapyphase 1/2a clinical trial

#13 of 7,789

5718m citations

Therapeutic targeting of cellular senescence in diabetic macular edema: preclinical and phase 1 trial results

Sergio Crespo-Garcia et al.Nature Medicine202410.1038/s41591-024-02802-4

CorrespondingPrzemysław SapiehaInstitutionUniversity of Montreal, Canada

cellular senescenceDiabetic macular edemaSenolytic therapyphase 1 clinical trialRetinal pigment epitheliumsenescence-associated secretory phenotypevascular endothelial growth factorOptical coherence tomographyCentral subfield thicknessp16INK4ap21SA-β-galactosidasedasatinibquercetinAnti-VEGF therapyDiabetic retinopathy

#14 of 7,789

5718m citations

Effect of Fenofibrate on Progression of Diabetic Retinopathy

David Preiss et al.NEJM Evidence202410.1056/evidoa2400179

CorrespondingDavid PreissInstitutionUniversity of Oxford, United Kingdom

fenofibrateDiabetic retinopathy predictionDiabetic macular edemaDiabetic retinopathy screeningDiabetic retinopathyIntravitreal injectionretinal laser treatmentvitrectomyScotland DES grading schemeimpaired renal functionearly retinal changes

#15 of 7,789

5418m citations

DRAC 2022: A public benchmark for diabetic retinopathy analysis on ultra-wide optical coherence tomography angiography images

Bo Qian et al.Patterns202410.1016/j.patter.2024.100929

CorrespondingHuating Li, Yih Chung Tham, Tien Yin Wong, Bin ShengInstitutionShanghai Jiao Tong University, China

Retinal image datasetOptical coherence tomography angiographyDRAC datasetImage segmentationImage quality assessmentDiabetic retinopathy classificationMICCAI 2022 challengeDiabetic retinopathy diagnosisbenchmark dataset for medical imagingpublic medical imaging challenge

#16 of 7,789

5218m citations

Autonomous artificial intelligence increases screening and follow-up for diabetic retinopathy in youth: the ACCESS randomized control trial

Risa M Wolf et al.Nature Communications202410.1038/s41467-023-44676-z

CorrespondingRisa M. WolfInstitutionJohns Hopkins School of Medicine, United States

autonomous artificial intelligenceDiabetic retinopathy screeningpediatric type 1 diabetespediatric type 2 diabetesdiabetic eye exam completion rateeye care provider referralScreening follow-upracially and ethnically diverse youth populationacademic pediatric diabetes centerparallel randomized controlled trialNCT05131451point-of-care screeninghealth disparities in diabetes carescripted eye care referral and educationyouth diabetes managementdiabetic complication prevention

#17 of 7,789

4918m citations

Intravitreal aflibercept 8 mg in diabetic macular oedema (PHOTON): 48-week results from a randomised, double-masked, non-inferiority, phase 2/3 trial

David M Brown et al.The Lancet202410.1016/s0140-6736(23)02577-1

CorrespondingSobha SivaprasadInstitutionRetina Consultants of Texas, United States

AfliberceptDiabetic macular edemaNoninferiority trial designExtended dosing intervalBest-corrected visual acuity (BCVA)Central subfield thicknessPHOTON trialAnti-VEGF therapy12-week and 16-week dosing regimens48-week efficacy outcomesphase 2/3 clinical trial

#18 of 7,789

4718m citations

Age-Related Macular Degeneration, a Mathematically Tractable Disease

Christine A Curcio et al.Investigative Ophthalmology & Visual Science202410.1167/iovs.65.3.4

CorrespondingChristine A. CurcioInstitutionUniversity of Alabama at Birmingham, United States

Age-related macular degenerationETDRS griddrusenPhotoreceptorsRetinal pigment epitheliummacula lutearod-mediated dark adaptationGeographic atrophyBruch's membraneChoroidflat mounted donor eyesxanthophyll pigmentphotopic visual acuityouter retina agingcentral subfield risknear-periphery rod densityneuroanatomical nomenclatureeye-tracked clinical imaging

#19 of 7,789

4318m citations

Severe Intraocular Inflammation Following Intravitreal Faricimab

Loka Thangamathesvaran et al.JAMA Ophthalmology202410.1001/jamaophthalmol.2024.0530

CorrespondingNeil M. BresslerInstitutionJohns Hopkins University, United States

FaricimabIntraocular inflammationSterile endophthalmitisNeovascular age-related macular degenerationbrolucizumabPegcetacoplanAfliberceptbevacizumabvitreous tapintravitreal ceftazidimeintravitreal vancomycinvitrectomyStaphylococcus epidermidis contaminantvisual acuity outcomesCase seriesdrug storage or handling problempost-marketing surveillancelot number cluster

#20 of 7,789

4318m citations

Glaucoma diagnosis from fundus images using modified Gauss-Kuzmin-distribution-based Gabor features in 2D-FAWT

Rajneesh Kumar Patel et al.Computers & Electrical Engineering202410.1016/j.compeleceng.2024.109538

CorrespondingSiddharth Singh ChouhanInstitutionVIT Bhopal University, India

Glaucoma diagnosisFundus image2D fractional Fourier-adjusted wavelet transform (2D-FAWT)Gauss-Kuzmin distributionGabor featuresFeature extraction

Topic trends

Dominant research themes and year-over-year shifts in Retinal Diseases and Treatments

What Topics Define the Class of 2026?

The informative word cloud across the 50 highest 18-month-cited retinal diseases and treatments papers reveals a field anchored in treatable retinal disease, anti-VEGF therapy evaluation, and multimodal imaging—not standalone deep-learning classification. Diabetic retinopathy leads at 12 of 50 papers (normalized frequency 0.24), followed by anti-VEGF therapy (11 papers, 0.22). Age-related macular degeneration, diabetic macular edema, and fundus image each appear in 9 papers (0.18), underscoring how disease entities, therapy trials, and structural imaging remain tightly coupled in influential 2024 work. Neovascular AMD and faricimab (8 papers each, 0.16) highlight sustained interest in wet AMD and next-generation VEGF-pathway agents. Mid-sized terms cluster around trial endpoints and delivery—best-corrected visual acuity, optical coherence tomography, aflibercept, intravitreal injection, and extended dosing interval—alongside diabetic retinopathy screening, inherited retinal degeneration, and geographic atrophy. Convolutional neural network–based classification appears but at reduced prominence (4 papers, 0.08) after informativeness filtering, while smaller visible terms—including diabetic retinopathy prediction, retinal pigment epithelium, photoreceptors, Leber congenital amaurosis, and angiopoietin-2 inhibition—signal growing citation weight for inherited disease, gene therapy, and bispecific anti-VEGF mechanisms alongside traditional trial designs.

How Did Topics Shift from the Class of 2025 to the Class of 2026?

Comparing normalized concept frequencies between the Class of 2025 (2023 publications) and Class of 2026 (2024 publications) cohorts shows a reorientation of early-high-impact research priorities within retinal medicine. Diabetic macular edema exhibited the largest gain (+0.12 normalized frequency; 3 versus 9 papers), followed by diabetic retinopathy prediction (+0.08; 0 versus 4), diabetic retinopathy screening (+0.08; 2 versus 6), and inherited retinal degeneration (+0.08; 2 versus 6). The topic evolution card underscores that Class of 2026 bars extend furthest for diabetic retinopathy, anti-VEGF therapy, diabetic macular edema, age-related macular degeneration, and diabetic retinopathy screening—topics aligned with expanded anti-VEGF trial programs, inherited disease gene therapy, and population screening infrastructure. Conversely, fundus image showed the steepest decline (−0.24; 21 versus 9 papers), reflecting reduced dominance of general fundus-imaging papers among top-cited work. Convolutional neural network–based diabetic retinopathy classification (−0.14), intravitreal injection framing (−0.08), and diabetic retinopathy classification (−0.08) also receded, alongside modest drops for complement inhibition and neovascular AMD. Together, these shifts suggest that the most-cited 2024 papers emphasize disease-specific therapy trials, inherited retinal disease, and clinical endpoints over standalone deep-learning classification and broad imaging dataset studies.

Methodology

PRI identifies high-impact research using a transparent, topic-agnostic framework applied consistently across scientific domains. Bibliographic records are drawn from OpenAlex, including publication dates, citation relationships, and document types.

This ranking covers the Class of 2026 cohort: journal articles published in 2024. Reviews and other non-article document types are excluded to ensure comparability.

Research impact is quantified with an 18-month post-publication citation window—the number of citing works published within 18 months of each paper's publication date. This metric captures early impact while controlling for publication age.

An LLM-based relevance classifier then reviews each candidate's title and abstract to confirm substantive alignment with the target domain. Only papers classified as relevant appear in the final ranking.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459

Full methodology GitHub bioRxiv preprint

Cite this ranking

Pepkio Research Index (PRI). Topics and Trends in Most Cited Retinal Diseases and Treatments Papers, Class of 2026. https://pri.pepkio.com/top-papers/retinal-diseases-and-treatments/2026. Accessed 2026-07-13.

Zheng Su, Tinsley Li, Thematic Shifts in Early-High-Impact Cancer Genomics and Diagnostics Research: A Bibliometric and Semantic Analysis. bioRxiv 2026.07.04.736459; doi: https://doi.org/10.64898/2026.07.04.736459

Source data

The full ranking corpus and analysis files are openly available on an external repository. Please cite the dataset below when reusing this data.

View source dataset →

PRI Team (2026). PRI results: Retinal Diseases and Treatments (T10170) — Class of 2025 and Class of 2026 cohorts [Data set]. Figshare. https://doi.org/10.6084/m9.figshare.32902781