Scholar4AI Updated 2026-11-05 06:02 UTC+09:00

BraTS

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data category: Medical and clinical datasets · 0 papers in the last 7 days

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Clinical records, medical images and physiological signals used in medical machine learning.

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Names searched for: BraTS

Key findings#

  • From Nov 2023 to Oct 2026, 224 archived papers mentioned BraTS in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Oct 2025 (11).
  • BraTS was mentioned in 1 paper in the last 30 days (2026-10-07 to 2026-11-05), ranking #165 of the 246 datasets mentioned.
  • By journal category: AI (1).
  • Most of them appeared in Knowledge and Information Systems (1).
  • From 2017 to 2026 (so far), BraTS was mentioned in 272 papers in the tracked journals, most of them in AI (229), management (13) and health economics and policy (8).
  • 75 of them were published in 2025, against 2 in 2017.
  • Since 2023, the institutions with the most of these papers were Université de Rouen Normandie (9), Hangzhou Normal University (8) and Analyse Intégrée Multimodale en Santé (7).
  • The journals publishing most of them were Expert Systems with Applications (27), Pattern Recognition (21) and Neural Computing and Applications (21).
  • The most-cited of them is “Medical Image Segmentation Review: The Success of U-Net” (IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024), with 1,065 citations.
  • Papers use BraTS most often with TCGA (27), ImageNet (26) and Kaggle (18); it has 25 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
TrendNov 23–Oct 24Nov 24–Oct 25Nov 25–Oct 2636 months
696986224

Papers per year#

2017: 2 papers2018: 1 paper2019: 3 papers2020: 7 papers2021: 6 papers2022: 14 papers2023: 23 papers2024: 68 papers2025: 75 papers2026 (so far): 73 papers
20172026 (so far)
Papers per publication year and category
Category2017201820192020202120222023202420252026 (so far)
AI213761416586656
Management0000003343
Health Economics and Policy0000001124
Economics0000000313
Higher Education and Research0000001102
Statistics0000001200
Finance0000000003
Operations Research0000000002
Information Systems0000001010
Tourism and Hospitality0000000010
All categories213761423687573

Where the papers come from#

Institutions with the most papers, since 2023
#InstitutionPapers
1Université de Rouen Normandie9
2Hangzhou Normal University8
3Analyse Intégrée Multimodale en Santé7
4Centre National de la Recherche Scientifique6
5Fudan University6
6Stanford University6
7University of Science and Technology of China6
8Hong Kong University of Science and Technology5
9Monash University5
10Shenzhen University5
Countries with the most papers, since 2023
#CountryPapers
1China93
2United States41
3United Kingdom31
4India23
5Australia18
6France18
7Italy17
8Canada14
9Germany14
10Hong Kong14
Keywords with the most papers, since 2023
#KeywordPapers
1brain tumor segmentation78
2BraTS62
3medical image segmentation32
4magnetic resonance imaging27
5multimodal MRI23
6BraTS 202020
73D medical image segmentation12
8U-Net12
9BraTS 202111
10attention mechanism11

Most-cited papers#

Most-cited papers since 2017
#CitationsPer monthTitleJournalPublishedAuthors
11,06540.2Medical Image Segmentation Review: The Success of U-NetIEEE Transactions on Pattern Analysis and Machine Intelligence2024-08-21Reza Azad, Ehsan Khodapanah Aghdam, Amelie Rauland et al.
259512.3Brain tumor segmentation based on the fusion of deep semantics and edge information in multimodal MRIInformation Fusion2022-10-27Zhiqin Zhu, Xianyu He, Guanqiu Qi et al.
352216.4Federated learning for medical image analysis: A surveyPattern Recognition2024-03-12Hao Guan, Pew‐Thian Yap, Andrea Bozoki et al.
449514.0A comprehensive survey on applications of transformers for deep learning tasksExpert Systems with Applications2023-11-22Saidul Islam, Hanae Elmekki, Ahmed Elsebai et al.
52923.9Cross-modality deep feature learning for brain tumor segmentationPattern Recognition2020-07-27Dingwen Zhang, Guohai Huang, Qiang Zhang et al.

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use BraTS most often with TCGA (27), ImageNet (26) and Kaggle (18); it has 25 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →

What papers use BraTS together with (at least 3 papers; lift 1 = chance)
Used withTypePapers using bothLift
TCGADataset2726.2
ImageNetDataset261.9
KaggleDataset185.5
MNIST / Fashion-MNISTDataset121.9
Chest X-ray (CheXpert, ChestX-ray14)Dataset1018.3
ISIC skin lesion archiveDataset1018.1
ADNIDataset96.5
CIFAR-10 / CIFAR-100Dataset91.1
WikipediaDataset91.6
LIDC-IDRIDataset616.0
MIMICDataset63.1
YouTube / TikTokDataset60.6
Papers mentioning BraTS in the last 30 days, newest first.
DateTitleJournalAuthorsAffiliations
2026-10-16Evaluating LLMs for named entity recognition: a cost-benefit analysis in the legal domainKnowledge and Information SystemsShefali Singhal, Eoin O’Connell, Niall McCarroll et al.University of Ulster; Ulster University, Derry-Londonderry Campus
Cite this page

Scholar4AI. (2026). BraTS. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/brats

@misc{scholar4ai-datasets-brats,
  author = {{Scholar4AI}},
  title = {BraTS},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/brats}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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