johnsmith88/heart-disease-dataset: papers linking to it

Kaggle · www.kaggle.com/datasets/johnsmith88/heart-disease-dataset

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Research papers in the 480 tracked journals that link to johnsmith88/heart-disease-dataset (https://www.kaggle.com/datasets/johnsmith88/heart-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 johnsmith88/heart-disease-dataset in their Crossref records, the first in 2023; most of them (4) in 2025.
By category: AI (7); the journals with the most are Knowledge-Based Systems (2), Neural Computing and Applications (2) and Applied Intelligence (1).

By year#

20232026

Papers linking to johnsmith88/heart-disease-dataset by publication year
Year	Papers
2023	1
2025	4
2026	2

Journals#

Journals whose papers link to johnsmith88/heart-disease-dataset most
Journal	Papers
Knowledge-Based Systems	2
Neural Computing and Applications	2
Applied Intelligence	1
Journal Of Big Data	1
Expert Systems with Applications	1

Papers linking to johnsmith88/heart-disease-dataset, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-01-12	Early identification of PCOS with commonly known diseases: Obesity, diabetes, high blood pressure and heart disease using machine learning techniques	Expert Systems with Applications	Shivani Aggarwal, Kavita Pandey	72	cites it
2025-02-27	Exploring the future of privacy-preserving heart disease prediction: a fully homomorphic encryption-driven logistic regression approach	Journal Of Big Data	Vankamamidi Srinivasa Naresh, Sivaranjani Reddi	28	cites it
2025-08-22	An autoencoder-based approach for feature engineering in cardiovascular disease prediction	Neural Computing and Applications	Amr E. Eldin Rashed, Mahmoud Badawy, Mostafa A. Elhosseini et al.	2	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
2026-03-03	Slack-Guided and Geometry-Aware (SGGA) Knowledge-Based oversampling for intelligent imbalanced learning	Knowledge-Based Systems	Reema Lalit, Kapil Gupta	1	cites it
2026-05-01	Community partitioning and node belonging prediction method based on neighborhood attribute reduction and fuzzy rough set with application in clinical decision making	Applied Intelligence	Haoran Sun, Xiangtang Chen, Bingzhen Sun et al.	1	cites it
2025-09-15	The role of explainable AI in building trust and acceptance of AI-driven heart disease	Neural Computing and Applications	Fatma M. Talaat, Wesam F. Aly, Rana Mohamed El-Balka 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). johnsmith88/heart-disease-dataset: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-johnsmith88-heart-disease-dataset

@misc{scholar4ai-code-kaggle-johnsmith88-heart-disease-dataset,
  author = {{Scholar4AI}},
  title = {johnsmith88/heart-disease-dataset: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-johnsmith88-heart-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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