datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
plism-dataset-tiles
PLISM dataset
The Pathology Images of Scanners and Mobilephones (PLISM) dataset was created by (Ochi et al., 2024) for the evaluation of AI models’ robustness to inter-institutional domain shifts.
All histopathological specimens used in creating the PLISM dataset were sourced from patients who were diagnosed and underwent surgery at the University of Tokyo Hospital between 1955 and 2018.
PLISM-wsi consists in a group of consecutive slides digitized under 7 different scanners and… See the full description on the dataset page: https://huggingface.co/datasets/owkin/plism-dataset-tiles.nanopath-fairness-tiles
nanopath-fairness-tiles
Pre-tiled histopathology patches from CPTAC whole-slide images, used as the
external out-of-distribution validation set for a study on pretraining-time
vs. post-hoc fairness in histopathology foundation models.
Contents
Per-cohort folders, each slides_full/<slide_id>.parquet (one row per tile:
case_id, slide_id, tile_idx, image) + labels.tsv:
cohort
organ / task
slides
cptac_lung
NSCLC — LUAD vs LSCC subtype
604
cptac_gbm
GBM —… See the full description on the dataset page: https://huggingface.co/datasets/ryankim17920/nanopath-fairness-tiles.plism-dataset-tiles-st
Stain-Transferred PLISM Dataset
Dataset Overview
The Stain-Transferred PLISM dataset is a synthetic variant of the PLISM dataset tiles provided by Filiot et al. (2025), which is based on the original PLISM-wsi dataset by Ochi et al. (2024).
This dataset isolates global color-level variations (staining profiles) from localized morphological and scanner-specific hardware artifacts. It is specifically designed to evaluate and robustify computational pathology… See the full description on the dataset page: https://huggingface.co/datasets/klotz11/plism-dataset-tiles-st.