Dogan, Refika SultanAkay, EbruDogan, SerkanYilmaz, Bulent2025-12-212025-12-2120252052-4463https://doi.org/10.1038/s41597-025-06168-1https://hdl.handle.net/20.500.12573/5716The dataset in this study includes 202 videos with a total of 422 minutes, reaching Kayseri City Hospital's gastroenterology department as colonoscopy videos and 1903 microscopy images between 2019 and 2021. It includes 399 colonoscopy, microscopy images, and pathological diagnoses of polyps, as well as immunohistochemical staining results for proteins that play an important role in the assessment of cancerous cells, such as staining results for p53 (clone: bp53-11), Ki-67 (clone: 30-9), CD34 (clone: QBend/10), PD-L1 (clone: SP142), BRAF (clone: V600E) and VEGF (clone: SP125). By sharing the data openly, we aim to facilitate benchmarking, exploratory analysis and transfer-learning studies on colorectal polyps and cancer. In combination with external datasets or pretrained models, the resource can help advance data-driven detection and characterisation work. The diverse range of polyps assigned to cancer stages from 201 patients makes this tool valuable for researchers and clinicians in furthering diagnosis and treatment.eninfo:eu-repo/semantics/openAccessVim-Polyp: Multimodal Colon Polyp Dataset with Video, Histopathology, and Protein ExpressionArticle10.1038/s41597-025-06168-12-s2.0-105023790490