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SMART redefines brain atlas construction by achieving state-of-the-art forecasting accuracy while maintaining interpretability and scalability in high-dimensional medical imaging.
Uncertainty quantification in MRI reconstruction can now be achieved with superior accuracy, revealing critical insights into image reliability that deep learning methods overlook.
Worsening of a specific lung abnormality called PPFE, easily measurable on routine lung cancer screening CT scans, strongly predicts earlier death and respiratory problems.
Prostate cancer diagnosis gets a boost: a new vision foundation model, ProFound, beats task-specific models across 11 clinical tasks after pre-training on a massive multi-institutional MRI dataset.
Unlock richer disease insights by modeling both discrete and continuous biomarkers simultaneously, revealing hidden subtypes and progression stages previously obscured by single-data-type limitations.
