jakeshbohaju/brain-tumor: papers linking to it

Kaggle · www.kaggle.com/datasets/jakeshbohaju/brain-tumor

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to jakeshbohaju/brain-tumor (https://www.kaggle.com/datasets/jakeshbohaju/brain-tumor), 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 jakeshbohaju/brain-tumor in their Crossref records, the first in 2025; most of them (3) in 2025.
By category: AI (3); the journals with the most are Neural Computing and Applications (3).

By year#

20252025

Papers linking to jakeshbohaju/brain-tumor by publication year
Year	Papers
2025	3

Journals#

Journals whose papers link to jakeshbohaju/brain-tumor most
Journal	Papers
Neural Computing and Applications	3

Papers linking to jakeshbohaju/brain-tumor, most cited first
Published	Title	Journal	Authors	Citations	Link
2025-02-28	Enhanced brain tumor detection and classification using a deep image recognition generative adversarial network (DIR-GAN): a comparative study on MRI, X-ray, and FigShare datasets	Neural Computing and Applications	S. Karpakam, N. Kumareshan	12	cites it
2025-06-18	Automated brain tumor detection using novel hybrid vision transformer and EfficientNetb4 models with comparative analysis	Neural Computing and Applications	S. Selva Karthik, V. Achuthan, Antony Dennis Ananth et al.	2	cites it
2025-05-07	Efficient and accurate brain tumor detection and classification using advanced hybrid filtering and self-attention generative adversarial networks	Neural Computing and Applications	R. Rajakumari, Selvapandian Arumugam	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). jakeshbohaju/brain-tumor: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-jakeshbohaju-brain-tumor

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

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