mlsanityData to 14 Oct 2026

Predicting Diabetic Macular Edema Treatment Responses Using OCT: Dataset and Methods of APTOS Competition

arXiv 2505.05768 ↗First posted 9 May 2025eess.IV cs.AI cs.CVcited by 3

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Abstract (arXiv)

Diabetic macular edema (DME) significantly contributes to visual impairment in diabetic patients. Treatment responses to intravitreal therapies vary, highlighting the need for patient stratification to predict therapeutic benefits and enable personalized strategies. To our knowledge, this study is the first to explore pre-treatment stratification for predicting DME treatment responses. To advance this research, we organized the 2nd Asia-Pacific Tele-Ophthalmology Society (APTOS) Big Data Competition in 2021. The competition focused on improving predictive accuracy for anti-VEGF therapy responses using ophthalmic OCT images. We provided a dataset containing tens of thousands of OCT images from 2,000 patients with labels across four sub-tasks. This paper details the competition's structure, dataset, leading methods, and evaluation metrics. The competition attracted strong scientific community participation, with 170 teams initially registering and 41 reaching the final round. The top-performing team achieved an AUC of 80.06%, highlighting the potential of AI in personalized DME treatment and clinical decision-making.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 21 of its 76 references that are in the map. First posted on arXiv 9 May 2025.

Builds on

21 of 76 references.

References · 21

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9 more
  1. 2023AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challengecited by 35
  2. 2022ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Imagescited by 25
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025Benchmarking Large Multimodal Models for Ophthalmic Visual Question Answering with OphthalWeChatcited by 2
  2. 2026Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Developmentcited by 2
  3. 2026EyeWorld: A Generative World Model of Ocular State and Dynamicscited by 0