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PANDA achieves a remarkable AUC of 0.893 in Alzheimer's classification, outperforming traditional methods even with zero auxiliary data at inference.
Achieving near state-of-the-art CXR detection with under 10% of the usual annotations could revolutionize medical imaging workflows.
A novel lightweight 3D detector achieves high organ localization accuracy in abdominal CT scans using pseudo-text conditioning, setting a new open-source benchmark.
Achieve state-of-the-art zero-shot chest X-ray classification by cleverly curating training data and distilling knowledge into CLIP models, sidestepping the need for large-scale retraining.
CNNs still reign supreme for medical image segmentation on heterogeneous datasets, beating out hybrid transformer models despite the latter's theoretical advantages.
