kmader/skin-cancer-mnist-ham10000: papers linking to it

Kaggle · www.kaggle.com/datasets/kmader/skin-cancer-mnist-ham10000

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to kmader/skin-cancer-mnist-ham10000 (https://www.kaggle.com/datasets/kmader/skin-cancer-mnist-ham10000), 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#

5 papers in the tracked journals link to the Kaggle dataset kmader/skin-cancer-mnist-ham10000 in their Crossref records, the first in 2023; most of them (2) in 2025.
By category: AI (5); the journals with the most are Knowledge-Based Systems (2), Neural Computing and Applications (2) and Cognitive Computation (1).

By year#

20232025

Papers linking to kmader/skin-cancer-mnist-ham10000 by publication year
Year	Papers
2023	2
2024	1
2025	2

Journals#

Journals whose papers link to kmader/skin-cancer-mnist-ham10000 most
Journal	Papers
Knowledge-Based Systems	2
Neural Computing and Applications	2
Cognitive Computation	1

Papers linking to kmader/skin-cancer-mnist-ham10000, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-05-19	EHR privacy preservation using federated learning with DQRE-Scnet for healthcare application domains	Knowledge-Based Systems	C. U. Om Kumar, Sudhakaran Gajendran, R.M. Bhavadharini et al.	34	cites it
2023-08-19	A novel uncertainty-aware deep learning technique with an application on skin cancer diagnosis	Neural Computing and Applications	Afshar Shamsi, Hamzeh Asgharnezhad, Ziba Bouchani et al.	25	cites it
2024-12-31	A dynamic ensemble learning based data mining framework for medical imbalanced big data	Knowledge-Based Systems	Rithani Mohan, R Prasanna Kumar, Altalbe Ali	11	cites it
2025-06-05	Application of ensemble learning models in computer-aided diagnosis of skin diseases	Neural Computing and Applications	Abu S. Asaduzzaman, Christian C. Thompson, Fadi N. Sibai et al.	10	cites it
2025-05-13	Enhancing Skin Disease Diagnosis: Light GBM-DMS Algorithm for Accurate Image Classification	Cognitive Computation	B. Kalpana, A. Senthilselvi, S. Muruganandam et al.	2	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). kmader/skin-cancer-mnist-ham10000: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-kmader-skin-cancer-mnist-ham10000

@misc{scholar4ai-code-kaggle-kmader-skin-cancer-mnist-ham10000,
  author = {{Scholar4AI}},
  title = {kmader/skin-cancer-mnist-ham10000: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-kmader-skin-cancer-mnist-ham10000}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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