uraninjo/augmented-alzheimer-mri-dataset-v2: papers linking to it

Kaggle · www.kaggle.com/datasets/uraninjo/augmented-alzheimer-mri-dataset-v2

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to uraninjo/augmented-alzheimer-mri-dataset-v2 (https://www.kaggle.com/datasets/uraninjo/augmented-alzheimer-mri-dataset-v2), 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 uraninjo/augmented-alzheimer-mri-dataset-v2 in their Crossref records, the first in 2024; most of them (2) in 2024.
By category: AI (3); the journals with the most are Applied Intelligence (2) and Expert Systems with Applications (1).

By year#

20242025

Papers linking to uraninjo/augmented-alzheimer-mri-dataset-v2 by publication year
Year	Papers
2024	2
2025	1

Journals#

Journals whose papers link to uraninjo/augmented-alzheimer-mri-dataset-v2 most
Journal	Papers
Applied Intelligence	2
Expert Systems with Applications	1

Papers linking to uraninjo/augmented-alzheimer-mri-dataset-v2, most cited first
Published	Title	Journal	Authors	Citations	Link
2024-01-28	EAFP-Med: An efficient adaptive feature processing module based on prompts for medical image detection	Expert Systems with Applications	Xiang Li, Long Lan, Husam Lahza et al.	6	cites it
2024-01-01	DBTN: An adaptive neural network for multiple-disease detection via imbalanced medical images distribution	Applied Intelligence	Xiang Li, Long Lan, Chang-Yong Sun et al.	1	cites it
2025-11-01	A visual state space Model-Based Cross-Domain adaptive detection method for imbalanced medical image distribution	Applied Intelligence	Xiang Li, Long Lan, Husam Lahza et al.	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). uraninjo/augmented-alzheimer-mri-dataset-v2: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-uraninjo-augmented-alzheimer-mri-dataset-v2

@misc{scholar4ai-code-kaggle-uraninjo-augmented-alzheimer-mri-dataset-v2,
  author = {{Scholar4AI}},
  title = {uraninjo/augmented-alzheimer-mri-dataset-v2: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/kaggle-uraninjo-augmented-alzheimer-mri-dataset-v2}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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