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The Haberman survival dataset comprises data from a study conducted at the Billings Hospital of the University of Chicago between 1958 and 1970, involving patients who underwent breast cancer surgery. The dataset attributes include patients' age at operation, year of operation, number of positive axillary nodes detected, and survival status.

The NuCLS dataset comprises over 220,000 annotated nuclei from breast cancer images, primarily for developing and validating nucleus detection, classification, and segmentation algorithms. Annotations were performed by pathologists, pathology residents, and medical students, covering both single‑observer and multi‑observer evaluations. The dataset consists of 1,744 entries, each containing high‑resolution RGB images, mask images, visualization images, and nucleus annotation coordinates, split into six folds with separate training and test subsets to assess cross‑institution generalization. It is suitable for image classification, detection, and segmentation tasks.