--- title: "johnsmith88/heart-disease-dataset: papers citing it" description: "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." url: https://scholar4ai.com/code/kaggle-johnsmith88-heart-disease-dataset markdown_url: https://scholar4ai.com/code/kaggle-johnsmith88-heart-disease-dataset.md license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/) share_text: "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. (as of 2026-11-03)" data_url: https://scholar4ai.com/data/rankings.json updated: 2026-11-03T14:43:26+09:00 window: 2026-10-05 to 2026-11-03 source: OpenAlex (CC0) --- # johnsmith88/heart-disease-dataset: papers linking to it 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. - Kaggle - https://www.kaggle.com/datasets/johnsmith88/heart-disease-dataset All repositories: https://scholar4ai.com/code.md ## 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 *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](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2 | | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 | | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 1 | | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | 1 | | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 1 | ## Papers *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](https://doi.org/10.1016/j.eswa.2023.119532) | [Expert Systems with Applications](https://scholar4ai.com/journals/expert-systems-with-applications.md) | 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](https://doi.org/10.1186/s40537-025-01098-6) | [Journal Of Big Data](https://scholar4ai.com/journals/journal-of-big-data.md) | Vankamamidi Srinivasa Naresh, Sivaranjani Reddi | 28 | cites it | | 2025-08-22 | [An autoencoder-based approach for feature engineering in cardiovascular disease prediction](https://doi.org/10.1007/s00521-025-11484-z) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 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](https://doi.org/10.1016/j.knosys.2025.114434) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 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](https://doi.org/10.1016/j.knosys.2026.115671) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 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](https://doi.org/10.1007/s10489-026-07258-2) | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 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](https://doi.org/10.1007/s00521-025-11629-0) | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 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 ```bibtex @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} } ``` License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).