trauma
Datasets
All datasets matching “trauma”rsna-2023-abdominal-trauma-detectionThis dataset is the preprocessed version of the dataset from RSNA 2023 Abdominal Trauma Detection Kaggle Competition.
It is tailored for segmentation and classification tasks. It contains 3 different configs as described below:
- segmentation: 206 instances where each instance includes a CT scan in NIfTI format, a segmentation mask in NIfTI format, and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
- classification: 4711 instances where each instance includes a CT scan in NIfTI format, target labels (e.g., extravasation, bowel, kidney, liver, spleen, any_injury), and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
- classification-with-mask: 206 instances where each instance includes a CT scan in NIfTI format, a segmentation mask in NIfTI format, target labels (e.g., extravasation, bowel, kidney, liver, spleen, any_injury), and its relevant metadata (e.g., patient_id, series_id, incomplete_organ, aortic_hu, pixel_representation, bits_allocated, bits_stored)
All CT scans and segmentation masks had already been resampled with voxel spacing (2.0, 2.0, 3.0) and thus its reduced file size.africa-synth-flooding-extreme-weather-trauma-all
Extreme Weather & Trauma (SSA) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: climate_environment - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Public datasets… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-flooding-extreme-weather-trauma-all.road-traffic-injury-trauma
Road Traffic Injury & Trauma (GCS, ISS, Prehospital, Emergency Care) | Africa (Electric Sheep Africa metadata inventory)
Size category: 10K<n<100K - Formats: csv - Sector: infrastructure_transport - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/road-traffic-injury-trauma.africa-synth-prehospital-trauma-care-all
Prehospital Trauma Care | Africa (World Health Organization)
Size category: 10K<n<100K - Formats: csv - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help researchers examine disease… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-synth-prehospital-trauma-care-all.clinical-quad-perfusion-buffer-lag-coupling-trauma-deterioration-v0.1
What this repo does
This dataset models the transition from compensated trauma physiology to systemic deterioration using a four-variable coupling structure.
The goal is to detect when trauma patients are drifting toward hemodynamic collapse before overt shock or organ failure occurs.
Trauma deterioration often unfolds as a cascade: perfusion declines, physiological reserves are consumed, treatment delays amplify instability, and organ systems begin to couple into systemic failure.… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-perfusion-buffer-lag-coupling-trauma-deterioration-v0.1.clinical-quad-perfusion-buffer-lag-coupling-trauma-deterioration-v0.5
What this repo does
This repository provides a Clarus v0.5 cascade recovery geometry dataset for trauma deterioration.
Earlier Clarus datasets focused on detecting cascade states and identifying instability boundaries.Version v0.5 introduces a recovery geometry layer that asks a deeper question:
Can the system still return to stability?
The task is binary classification over trauma-linked deterioration states using:
• a four-variable clinical quad• trajectory dynamics• boundary… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-perfusion-buffer-lag-coupling-trauma-deterioration-v0.5.