TorchXRayVision
An open-source deep learning library for chest X-rays that gathers model weights pretrained on multiple large public datasets, unifies label systems and preprocessing workflows, and lowers the barrier to medical imaging AI development.
Timeline (last 90 days)
MedScribe AI uses a ResNet18 model trained on the Kaggle pediatric chest X-ray dataset at its foundation, and with the help of the TorchXRayVision open-source medical imaging foundation model, achieves 90.5% accuracy, 98.4% precision, and 93.2% F1 score according to data published by the project team.
TorchXRayVision is an open-source deep learning library for chest X-rays that gathers model weights pretrained on multiple public datasets (such as NIH ChestX-ray14, CheXpert, MIMIC-CXR, etc.) and unifies the label systems and preprocessing pipelines of different datasets.
All Facts (2)
MedScribe AI uses a ResNet18 model trained on the Kaggle pediatric chest X-ray dataset at its foundation, and with the help of the TorchXRayVision open-source medical imaging foundation model, achieves 90.5% accuracy, 98.4% precision, and 93.2% F1 score according to data published by the project team.
50%UnverifiedTorchXRayVision is an open-source deep learning library for chest X-rays that gathers model weights pretrained on multiple public datasets (such as NIH ChestX-ray14, CheXpert, MIMIC-CXR, etc.) and unifies the label systems and preprocessing pipelines of different datasets.
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