sulianova/cardiovascular-disease-dataset: papers linking to it

Kaggle · www.kaggle.com/datasets/sulianova/cardiovascular-disease-dataset

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Research papers in the 480 tracked journals that link to sulianova/cardiovascular-disease-dataset (https://www.kaggle.com/datasets/sulianova/cardiovascular-disease-dataset), 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#

7 papers in the tracked journals link to the Kaggle dataset sulianova/cardiovascular-disease-dataset in their Crossref records, the first in 2021; most of them (5) in 2025.
By category: AI (6) and Operations Research (1); the journals with the most are Knowledge-Based Systems (2), Knowledge and Information Systems (2) and Optimization and Engineering (1).

By year#

20212025

Papers linking to sulianova/cardiovascular-disease-dataset by publication year
Year	Papers
2021	1
2024	1
2025	5

Journals#

Journals whose papers link to sulianova/cardiovascular-disease-dataset most
Journal	Papers
Knowledge-Based Systems	2
Knowledge and Information Systems	2
Optimization and Engineering	1
Pattern Recognition	1
Cognitive Computation	1

Papers linking to sulianova/cardiovascular-disease-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-07-22	An adaptive and late multifusion framework in contextual representation based on evidential deep learning and Dempster–Shafer theory	Knowledge and Information Systems	Doaa Mohey El-Din, Aboul Ella Hassanein, Ehab E. Hassanien	13	cites it
2025-01-25	Augmenting Cardiovascular Disease Prediction Through CWCF Integration Leveraging Harris Hawks Search in Deep Belief Networks	Cognitive Computation	S. Savitha, A. Rajiv Kannan, K. Logeswaran	13	cites it
2021-01-06	Eigen-stratified models	Optimization and Engineering	Jonathan Tuck, Stephen Boyd	5	cites it
2025-05-12	Efficient healthcare data classification through gazelle-inspired optimization and multimodal deep learning	Knowledge and Information Systems	J. Arockia Jaya, K. Mahalakshmi	4	cites it
2025-07-28	A novel score function for conformal prediction in rule-based binary classification	Pattern Recognition	Sara Narteni, Alberto Carlevaro, Fabrizio Dabbene et al.	3	cites it
2025-08-12	Cardiac disease detection utilizing temporal attention recurrent graph convolutional neural network based smart wearable system	Knowledge-Based Systems	Mr Jibin E P, Dr Menaka D	1	cites it
2025-09-07	Development of an enhanced heart attack diagnosis model using knowledge distillation and frequent sequence pattern mining	Knowledge-Based Systems	Dinesh Kumar Bhawnani, Sunita Soni, Arpana Rawal	1	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). sulianova/cardiovascular-disease-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-sulianova-cardiovascular-disease-dataset

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

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