paultimothymooney/blood-cells: papers linking to it

Kaggle · www.kaggle.com/datasets/paultimothymooney/blood-cells

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to paultimothymooney/blood-cells (https://www.kaggle.com/datasets/paultimothymooney/blood-cells), 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#

4 papers in the tracked journals link to the Kaggle dataset paultimothymooney/blood-cells in their Crossref records, the first in 2020; most of them (3) in 2024.
By category: AI (3) and Information Systems (1); the journals with the most are Neural Computing and Applications (2), Telematics and Informatics Reports (1) and Expert Systems with Applications (1).

By year#

20202024

Papers linking to paultimothymooney/blood-cells by publication year
Year	Papers
2020	1
2024	3

Journals#

Journals whose papers link to paultimothymooney/blood-cells most
Journal	Papers
Neural Computing and Applications	2
Telematics and Informatics Reports	1
Expert Systems with Applications	1

Papers linking to paultimothymooney/blood-cells, most cited first
Published	Title	Journal	Authors	Citations	Link
2020-01-16	An Automatic Nucleus Segmentation and CNN Model based Classification Method of White Blood Cell	Expert Systems with Applications	Partha Pratim Banik, Rappy Saha, Ki‐Doo Kim	189	cites it
2024-02-28	Leukemia classification using different CNN-based algorithms-comparative study	Neural Computing and Applications	Areen K. Al‐Bashir, Ruba Khnouf, Lamis R. Bany Issa	24	cites it
2024-09-17	A deep learning approach for white blood cells image generation and classification using SRGAN and VGG19	Telematics and Informatics Reports	Jannatul Ferdousi, Soyabul Islam Lincoln, Md. Khorshed Alom et al.	20	cites it
2024-08-14	HMedCaps: a new hybrid capsule network architecture for complex medical images	Neural Computing and Applications	Sümeyra Büşra Şengül, İlker Ali Özkan	4	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). paultimothymooney/blood-cells: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/kaggle-paultimothymooney-blood-cells

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

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