aptos2019-blindness-detection: papers linking to it

Kaggle · www.kaggle.com/competitions/aptos2019-blindness-detection

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to aptos2019-blindness-detection (https://www.kaggle.com/competitions/aptos2019-blindness-detection), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

19 papers in the tracked journals link to the Kaggle dataset aptos2019-blindness-detection in their Crossref records, the first in 2022; most of them (6) in 2023.
By category: AI (19); the journals with the most are Expert Systems with Applications (5), Neural Computing and Applications (4) and Knowledge-Based Systems (2).
4 of the papers build on one another: a later paper cites an earlier one that also links aptos2019-blindness-detection.

By year#

20222026

Papers linking to aptos2019-blindness-detection by publication year
Year	Papers
2022	2
2023	6
2024	2
2025	5
2026	4

Journals#

Journals whose papers link to aptos2019-blindness-detection most
Journal	Papers
Expert Systems with Applications	5
Neural Computing and Applications	4
Knowledge-Based Systems	2
Artificial Intelligence Review	2
Information Fusion	2

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Diabetic retinopathy identification using parallel convolutional neural network based feature extractor and ELM classifier Expert Systems with Applications, 2023
- Two-stage framework for diabetic retinopathy diagnosis and disease stage screening with ensemble learning Expert Systems with Applications, 2023 — cites the paper above
Automated detecting and severity grading of diabetic retinopathy using transfer learning and attention mechanism Neural Computing and Applications, 2023
- DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network Journal Of Big Data, 2024 — cites the paper above

Papers linking to aptos2019-blindness-detection, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-01-13	Diabetic retinopathy identification using parallel convolutional neural network based feature extractor and ELM classifier	Expert Systems with Applications	Md. Nahiduzzaman, Md. Robiul Islam, Md. Omaer Faruq Goni et al.	142	cites it
2023-12-19	CTNet: convolutional transformer network for diabetic retinopathy classification	Neural Computing and Applications	Ruchika Bala, Arun Sharma, Nidhi Goel	36	cites it
2025-05-09	Enhanced multi-grade diabetic retinopathy detection and classification via ensembled deep learning model from retinal fundus images	Expert Systems with Applications	Peddapullaiahgari Hariobulesu, Fahimuddin Shaik	30	cites it
2023-04-20	Two-stage framework for diabetic retinopathy diagnosis and disease stage screening with ensemble learning	Expert Systems with Applications	Mohammad H. Alshayeji, Sa’ed Abed, Silpa ChandraBhasi Sindhu	23	cites it
2022-12-16	Joint grading of diabetic retinopathy and diabetic macular edema using an adaptive attention block and semisupervised learning	Applied Intelligence	Xiaoxin Guo, Xiang Li, Qifeng Lin et al.	22	cites it
2023-09-11	Automated detecting and severity grading of diabetic retinopathy using transfer learning and attention mechanism	Neural Computing and Applications	Maryam Dinpajhouh, Seyyed Ali Seyyedsalehi	22	cites it
2022-11-05	Diabetic retinopathy classification based on dense connectivity and asymmetric convolutional neural network	Neural Computing and Applications	Juan Cao, Jiaran Chen, Xinying Zhang et al.	13	cites it
2023-06-28	AO-HRCNN: archimedes optimization and hybrid region-based convolutional neural network for detection and classification of diabetic retinopathy	Artificial Intelligence Review	Sujatha Krishnamoorthy, yu Weifeng, Luo Jin et al.	11	cites it
2024-08-03	DiabSense: early diagnosis of non-insulin-dependent diabetes mellitus using smartphone-based human activity recognition and diabetic retinopathy analysis with Graph Neural Network	Journal Of Big Data	Md Nuho Ul Alam, Ibrahim Hasnine, Erfanul Hoque Bahadur et al.	9	cites it
2025-12-20	DualAttendMed: A coarse-to-fine dual-stage attention framework for interpretable disease localization and classification	Expert Systems with Applications	Junaid Abbas, Danyal Badar Soomro, Shanshan Huang et al.	9	cites it
2023-09-13	ESOA-HGRU: egret swarm optimization algorithm-based hybrid gated recurrent unit for classification of diabetic retinopathy	Artificial Intelligence Review	Abrar Mohammed Alajlan, Abdul Razaque	8	cites it
2024-05-06	Pathologic myopia diagnosis and localization from retinal fundus images using custom CNN	Neural Computing and Applications	Pammi Kumari, Priyank Saxena	6	cites it
2025-07-07	Bi-branch bidirectional coupled interaction fusion network for multi-retinal diseases diagnosis	Knowledge-Based Systems	Shaobin Chen, Tao Tan, Xinyu Zhao et al.	2	cites it
2026-04-30	RobustDRNet: A clinically-aligned hybrid ensemble model with multi-method explainability for lesion-aware diabetic retinopathy grading	Expert Systems with Applications	Pir Bakhsh Khokhar, Viviana Pentangelo, Carmine Gravino et al.	2	cites it
2025-05-13	OBoctNet: Enhancing Ophthalmic Biomarker Detection Through Active Learning and Explainable AI in Radiological Analysis	Cognitive Computation	Samya Acharja, Md. Tanvir Rahman, Farjana Haque Chamok et al.	1	cites it
2026-04-01	Towards reliable medical unsupervised anomaly detection: A benchmark and dataset for PET/CT with cross-modality knowledge distillation network	Information Fusion	Muhao Xu, Lili Qu, Zihan Nie et al.	1	cites it
2026-04-15	A large-scale multi-view fundus images dataset and benchmark for diabetic retinopathy grading	Information Fusion	Xiaoling Luo, Qiaojian Zheng, Chengliang Liu et al.	1	cites it
2025-10-06	Analysis of model-based ensemble learning for accurate diabetic retinopathy grading	Knowledge-Based Systems	Huang-Chia Shih, Yuchang Cheng, Chia-Shiang Chen et al.	0	cites it
2026-07-21	MRM++: Enhanced Masked Relation Modeling for Multi-Modal Medical Pre-training	International Journal of Computer Vision	Qiushi Yang, Wuyang Li, Zhe Peng et al.	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). aptos2019-blindness-detection: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-competition-aptos2019-blindness-detection

@misc{scholar4ai-code-kaggle-competition-aptos2019-blindness-detection,
  author = {{Scholar4AI}},
  title = {aptos2019-blindness-detection: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-competition-aptos2019-blindness-detection}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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