kmader/finding-lungs-in-ct-data: papers linking to it

Kaggle · www.kaggle.com/datasets/kmader/finding-lungs-in-ct-data

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to kmader/finding-lungs-in-ct-data (https://www.kaggle.com/datasets/kmader/finding-lungs-in-ct-data), 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/finding-lungs-in-ct-data in their Crossref records, the first in 2021; most of them (2) in 2021.
By category: AI (5); the journals with the most are Neural Computing and Applications (2), Knowledge-Based Systems (1) and Applied Intelligence (1).

By year#

20212025

Papers linking to kmader/finding-lungs-in-ct-data by publication year
Year	Papers
2021	2
2022	1
2023	1
2025	1

Journals#

Journals whose papers link to kmader/finding-lungs-in-ct-data most
Journal	Papers
Neural Computing and Applications	2
Knowledge-Based Systems	1
Applied Intelligence	1
Pattern Recognition	1

Papers linking to kmader/finding-lungs-in-ct-data, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-06-01	Lung segmentation and automatic detection of COVID-19 using radiomic features from chest CT images	Pattern Recognition	Zhao Chen, Yan Xu, Zhuo He et al.	110	cites it
2022-04-25	Semantic segmentation in medical images through transfused convolution and transformer networks	Applied Intelligence	Tashvik Dhamija, Anunay Gupta, Shreyansh Gupta et al.	74	cites it
2023-03-26	DoubleU-NetPlus: a novel attention and context-guided dual U-Net with multi-scale residual feature fusion network for semantic segmentation of medical images	Neural Computing and Applications	Md. Rayhan Ahmed, Md. Rayhan Ahmed, Adnan Ferdous Ashrafi et al.	34	cites it
2021-03-18	Medical image segmentation based on active fusion-transduction of multi-stream features	Knowledge-Based Systems	Yucheng Shu, Jing Zhang, Bin Xiao et al.	28	cites it
2025-01-06	Masked hybrid attention with Laplacian query fusion and tripartite sequence matching for medical image segmentation	Neural Computing and Applications	Favour Ekong, Yongbin Yu, Rutherford Agbeshi Patamia 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/finding-lungs-in-ct-data: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-kmader-finding-lungs-in-ct-data

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

Free to reuse for non-commercial purposes with attribution (CC BY-NC 4.0).