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| Dataset/service/project | Link | Type(s) of cancer(s) | Description |
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| TCGA database | https://www.cancer.gov/aboutnci/organization/ccg/research/structural-genomics/tcga | Multiple | 33 cancer types, total no. of cases is 11125 |
| Rotterdam tumor bank | https://stat.ethz.ch/R-manual/R-devel/library/survival/html/rotterdam.html | Breast cancer | 2982 primary breast cancer patients; 1546 are positive cases |
| SUPPORT database | [31] | Multiple | 9105 adults, an overall 6-month mortality rate of 47% |
| METABRIC dataset | https://www.cbioportal.org/study/summary?id=brca_metabric | Breast cancer | 2509 primary breast tumor subjects, 548 matched normal control subjects |
| MITOS-ATYPIA-14 dataset | https://mitos-atypia-14.grand-challenge.org/Home/ | Breast cancer | Resolution of pixels at 20x and 40x magnification levels |
| TUPAC 2016 dataset | [33] | Breast cancer | 500 training and 321 testing breast cancer histology whole-brain slides |
| INbreast dataset | [34] | Breast cancer | Total of 115 cases and 410 images |
| LIDC-IDRI database | https://wiki.cancerimagingarchive.net/display/Public/LIDCIDRI#1966254194132fe653e4a7db00715f6f775c012 | Lung cancer | CT scans of 1018 subjects, three categories (i) mm, (ii) mm, and (iii) mm |
| LUNA16 dataset | https://luna16.grandchallenge.org/Data/ | Lung cancer | 888 CT scans, facilitates segmentation studies |
| BreakHis dataset | https://web.inf.ufpr.br/vri/databases/breast-cancerhistopathological-database-breakhis/ | Breast cancer | 9109 microscopic images; four different magnification levels which are 40x, 100x, 200x, and 400x collected from 82 subjects |
| 2015 Bioimaging Breast Histology Classification Challenge | https://rdm.inesctec.pt/dataset/nis-2017-003 | Breast cancer | Four classes which are normal, benign, in situ carcinoma, and invasive carcinoma; resolution of pixels |
| CAMELYON dataset | https://camelyon17.grand-challenge.org | Breast cancer | Facilitates patient-level analysis; 1399 unique whole-slide images; no metastases, macrometastases, micrometastases, and isolated tumor cells |
| PatchCamelyon dataset | https://www.tensorflow.org/datasets/catalog/patch_camelyon | Breast cancer | 327,680 color images with resolution of pixels; bigger than CIFAR10 and smaller than ImageNet dataset |
| 2018 ICIAR dataset | https://iciar2018-challenge.grand-challenge.org/Dataset/ | Breast cancer | Represent normal, benign, in situ carcinoma, and invasive carcinoma; 400 microscopy images with 100 images per class |
| MITOS12 dataset | http://ludo17.free.fr/mitos_2012/dataset.html | Breast cancer | 50 biopsy slides; 40x magnification level; more than 300 mitoses |
| Leukemia microarray gene data | https://www.bioconductor.org/packages/devel/data/experiment/manuals/leukemiasEset/man/leukemiasEset.pdf | Bone marrow cancer | 60 bone marrow samples; acute lymphoblastic leukemia, acute myeloid leukemia, chronic lymphocytic leukemia, chronic myeloid leukemia, and healthy bone marrow |
| Gene Expression Omnibus repository | https://www.ncbi.nlm.nih.gov/geo/ | Multiple | Provides comprehensive sets of microarray, next-generation sequencing, and other genomic data |
| BioGPS data portal | http://biogps.org/#goto=welcome | Multiple | Supports eight species including humans; supports different types of cancers |
| TCIA | https://www.cancerimagingarchive.net | Multiple | Supports a large number of modalities; supports data such as patient outcomes, treatment details, and genomics |
| GDC | https://gdc.cancer.gov | Multiple | Provides genomic, clinical, and biospecimen data |
| TARGET | https://ocg.cancer.gov/programs/target# | Multiple | Childhood cancers are supported; provides vast amounts of genomic data to estimate molecular alterations |
| 1000 Genomes Project | https://www.internationalgenome.org/1000-genomes-summary | Multiple | Provides a comprehensive resource on human genetic variation |
| Kvasir dataset | https://dl.acm.org/do/10.1145/3193289/abs/ | Gastrointestinal tract cancer | 4000 annotated images belonging to 8 classes |
| UCSB-BB dataset | https://bioimage.ucsb.edu/research/bio-segmentation | Supports breast cancer research in human species | Contains images of human, monkey, and cat species at subcellular, cellular, and tissue levels |
| BRATS dataset | https://www.med.upenn.edu/cbica/brats2020/ | Brain tumor | MRI scans of 65 subjects each in clinical and synthetic datasets, for brain tumor segmentation task |
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