Datasetpublic

Data-Gouv-ML/dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk

Dataset to develop diagnostic and predictive tools addressing IA rupture risk. Source Source officielle : https://www.data.gouv.fr/datasets/dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk Identifiant du jeu de données data.gouv.fr : 685e9f0c6058f64a66a02674 Slug data.gouv.fr : dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk Licence indiquée dans les métadonnées data.gouv.fr : cc-by-sa… See the full description on the dataset page: https://huggingface.co/datasets/Data-Gouv-ML/dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk.

sourceHugging Faceotherupdated 3mo agoView on Hugging Face

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Dataset Card

Dataset to develop diagnostic and predictive tools addressing IA rupture risk.

Source

—Source officielle : https://www.data.gouv.fr/datasets/dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk
—Identifiant du jeu de données data.gouv.fr : 685e9f0c6058f64a66a02674
—Slug data.gouv.fr : dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk
—Licence indiquée dans les métadonnées data.gouv.fr : cc-by-sa

Structure Hugging Face

—Un jeu de données data.gouv.fr = un dépôt Hugging Face
—Une ressource tabulaire d’origine = un sous-ensemble/configuration Hugging Face
—Chaque sous-ensemble/configuration contient un split nommé train

Sous-ensembles

—echantillons-de-donnee-genetiqyes-anonymes-synthetqiues → data/echantillons-de-donnee-genetiqyes-anonymes-synthetqiues.parquet
—jeux-de-donnees-synthetiques-anonymes → data/jeux-de-donnees-synthetiques-anonymes.parquet

Utilisation

python

from datasets import load_dataset

# Choisir un sous-ensemble/configuration :
ds = load_dataset("Data-Gouv-ML/dataset-to-develop-diagnostic-and-predictive-tools-addressing-ia-rupture-risk", "echantillons-de-donnee-genetiqyes-anonymes-synthetqiues")
print(ds["train"])

Description originale

ICAN (<https://doi.org/10.1093/neuros/nyw135>) is a French research program aimed at better understanding the pathophysiology of intracranial aneurysm (IA). One of the addressed challenges is to develop diagnostic and predictive tools addressing IA rupture risk. For computational reproducibility, we provide here a simulated clinical dataset tooled with Python and R notebooks. This material supports the paper "Location of intracranial aneurysms is the main factor associated with rupture in the ICAN population" published at <https://jnnp.bmj.com/content/92/2/122.abstract>.