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Found 3 papers, 1 papers with code
Interpretable Survival Analysis for Heart Failure Risk Prediction
Specifically, we use an improved version of survival stacking to transform a survival analysis problem to a classification problem, ControlBurn to perform feature selection, and Explainable Boosting Machines to generate interpretable predictions.
Metadata-Conditioned Generative Models to Synthesize Anatomically-Plausible 3D Brain MRIs
Generative AI models hold great potential in creating synthetic brain MRIs that advance neuroimaging studies by, for example, enriching data diversity.
Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model
As acquiring MRIs is expensive, neuroscience studies struggle to attain a sufficient number of them for properly training deep learning models.
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