IDEAS home Printed from https://ideas.repec.org/a/gam/jdataj/v10y2025i7p99-d1686370.html
   My bibliography  Save this article

Dataset and AI Workflow for Deep Learning Image Classification of Ulcerative Colitis and Colorectal Cancer

Author

Listed:
  • Joaquim Carreras

    (Department of Pathology, School of Medicine, Tokai University, 143 Shimokasuya, Isehara 259-1193, Kanagawa, Japan)

  • Giovanna Roncador

    (Monoclonal Antibodies Unit, Spanish National Cancer Research Center (CNIO), Melchor Fernandez Almagro 3, 28029 Madrid, Spain)

  • Rifat Hamoudi

    (Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Biomedically Informed Artificial Intelligence Laboratory (BIMAI-Lab), University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Center of Excellence for Precision Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
    Division of Surgery and Interventional Science, University College London, London NW3 2PF, UK)

Abstract

Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal tract characterized by the deregulation of immuno-oncology markers. IBD includes ulcerative colitis and Crohn’s disease. Chronic active inflammation is a risk factor for the development of colorectal cancer (CRC). This technical note describes a dataset of histological images of ulcerative colitis, CRC (adenocarcinoma), and colon control. The samples were stained with hematoxylin and eosin (H&E), and immunohistochemically analyzed for LAIR1 and TOX2 markers. The methods used for collecting, processing, and analyzing scientific data, including this dataset, using convolutional neural networks (CNNs) and information about the dataset’s use are also described. This article is a companion to the manuscript “Ulcerative Colitis, LAIR1 and TOX2 Expression, and Colorectal Cancer Deep Learning Image Classification Using Convolutional Neural Networks”.

Suggested Citation

  • Joaquim Carreras & Giovanna Roncador & Rifat Hamoudi, 2025. "Dataset and AI Workflow for Deep Learning Image Classification of Ulcerative Colitis and Colorectal Cancer," Data, MDPI, vol. 10(7), pages 1-30, June.
    • Handle: RePEc:gam:jdataj:v:10:y:2025:i:7:p:99-:d:1686370
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2306-5729/10/7/99/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2306-5729/10/7/99/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daniel B. Graham & Ramnik J. Xavier, 2020. "Pathway paradigms revealed from the genetics of inflammatory bowel disease," Nature, Nature, vol. 578(7796), pages 527-539, February.
    2. Bernard Khor & Agnès Gardet & Ramnik J. Xavier, 2011. "Genetics and pathogenesis of inflammatory bowel disease," Nature, Nature, vol. 474(7351), pages 307-317, June.
    3. Hanwen Xu & Naoto Usuyama & Jaspreet Bagga & Sheng Zhang & Rajesh Rao & Tristan Naumann & Cliff Wong & Zelalem Gero & Javier González & Yu Gu & Yanbo Xu & Mu Wei & Wenhui Wang & Shuming Ma & Furu Wei , 2024. "A whole-slide foundation model for digital pathology from real-world data," Nature, Nature, vol. 630(8015), pages 181-188, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hagar Taman & Christopher G Fenton & Endre Anderssen & Jon Florholmen & Ruth H Paulssen, 2021. "DNA hypo-methylation facilitates anti-inflammatory responses in severe ulcerative colitis," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-17, April.
    2. Zhaochang Yang & Ting Wei & Ying Liang & Xin Yuan & RuiTian Gao & Yujia Xia & Jie Zhou & Yue Zhang & Zhangsheng Yu, 2025. "A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    3. Gabriele Campanella & Shengjia Chen & Manbir Singh & Ruchika Verma & Silke Muehlstedt & Jennifer Zeng & Aryeh Stock & Matt Croken & Brandon Veremis & Abdulkadir Elmas & Ivan Shujski & Noora Neittaanmä, 2025. "A clinical benchmark of public self-supervised pathology foundation models," Nature Communications, Nature, vol. 16(1), pages 1-12, December.
    4. Fahad M. Aldakheel, 2021. "Allergic Diseases: A Comprehensive Review on Risk Factors, Immunological Mechanisms, Link with COVID-19, Potential Treatments, and Role of Allergen Bioinformatics," IJERPH, MDPI, vol. 18(22), pages 1-29, November.
    5. Antonella Gagliardi & Valentina Totino & Fatima Cacciotti & Valerio Iebba & Bruna Neroni & Giulia Bonfiglio & Maria Trancassini & Claudio Passariello & Fabrizio Pantanella & Serena Schippa, 2018. "Rebuilding the Gut Microbiota Ecosystem," IJERPH, MDPI, vol. 15(8), pages 1-24, August.
    6. Xingxing Ren & Qiuyuan Liu & Peirong Zhou & Tingyue Zhou & Decai Wang & Qiao Mei & Richard A. Flavell & Zhanju Liu & Mingsong Li & Wen Pan & Shu Zhu, 2024. "DHX9 maintains epithelial homeostasis by restraining R-loop-mediated genomic instability in intestinal stem cells," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    7. Zhilong Weng & Alexander Seper & Alexey Pryalukhin & Fabian Mairinger & Claudia Wickenhauser & Marcus Bauer & Lennert Glamann & Hendrik Bläker & Thomas Lingscheidt & Wolfgang Hulla & Danny Jonigk & Si, 2024. "GrandQC: A comprehensive solution to quality control problem in digital pathology," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    8. Atle van Beelen Granlund & Arnar Flatberg & Ann E Østvik & Ignat Drozdov & Bjørn I Gustafsson & Mark Kidd & Vidar Beisvag & Sverre H Torp & Helge L Waldum & Tom Christian Martinsen & Jan Kristian Damå, 2013. "Whole Genome Gene Expression Meta-Analysis of Inflammatory Bowel Disease Colon Mucosa Demonstrates Lack of Major Differences between Crohn's Disease and Ulcerative Colitis," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-14, February.
    9. Eduard Chelebian & Christophe Avenel & Carolina Wählby, 2025. "Combining spatial transcriptomics with tissue morphology," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    10. Luyang Luo & Mingxiang Wu & Mei Li & Yi Xin & Qiong Wang & Varut Vardhanabhuti & Winnie CW Chu & Zhenhui Li & Juan Zhou & Pranav Rajpurkar & Hao Chen, 2025. "A large model for non-invasive and personalized management of breast cancer from multiparametric MRI," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    11. Juan Manuel Zambrano Chaves & Shih-Cheng Huang & Yanbo Xu & Hanwen Xu & Naoto Usuyama & Sheng Zhang & Fei Wang & Yujia Xie & Mahmoud Khademi & Ziyi Yang & Hany Awadalla & Julia Gong & Houdong Hu & Jia, 2025. "A clinically accessible small multimodal radiology model and evaluation metric for chest X-ray findings," Nature Communications, Nature, vol. 16(1), pages 1-15, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jdataj:v:10:y:2025:i:7:p:99-:d:1686370. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.