abhranta/brain-tumor-detection-mri: papers linking to it

Kaggle · www.kaggle.com/datasets/abhranta/brain-tumor-detection-mri

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to abhranta/brain-tumor-detection-mri (https://www.kaggle.com/datasets/abhranta/brain-tumor-detection-mri), 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#

3 papers in the tracked journals link to the Kaggle dataset abhranta/brain-tumor-detection-mri in their Crossref records, the first in 2022; most of them (1) in 2024.
By category: AI (3); the journals with the most are Expert Systems with Applications (2) and Artificial Intelligence Review (1).

By year#

20222024

Papers linking to abhranta/brain-tumor-detection-mri by publication year
Year	Papers
2022	1
2023	1
2024	1

Journals#

Journals whose papers link to abhranta/brain-tumor-detection-mri most
Journal	Papers
Expert Systems with Applications	2
Artificial Intelligence Review	1

Papers linking to abhranta/brain-tumor-detection-mri, most cited first
Published	Title	Journal	Authors	Citations	Link
2023-10-18	Development of hybrid models based on deep learning and optimized machine learning algorithms for brain tumor Multi-Classification	Expert Systems with Applications	Muhammed ÇELİK, Özkan İni̇k	153	cites it
2022-12-15	A variate brain tumor segmentation, optimization, and recognition framework	Artificial Intelligence Review	Hossam Magdy Balaha, Asmaa El-Sayed Hassan	33	cites it
2024-11-22	Improving brain MRI denoising using convolutional AutoEncoder and sparse representations	Expert Systems with Applications	A. Velayudham, K. M. V. Madan Kumar, MS Krishna Priya	12	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). abhranta/brain-tumor-detection-mri: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-abhranta-brain-tumor-detection-mri

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

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