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Found 4 papers, 4 papers with code
Mind the Gap: Federated Learning Broadens Domain Generalization in Diagnostic AI Models
So far, the impact of training strategy, i. e., local versus collaborative, on the diagnostic on-domain and off-domain performance of AI models interpreting chest radiographs has not been assessed.
Preserving privacy in domain transfer of medical AI models comes at no performance costs: The integral role of differential privacy
We specifically investigate the performance of models trained with DP as compared to models trained without DP on data from institutions that the model had not seen during its training (i. e., external validation) - the situation that is reflective of the clinical use of AI models.
Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels
Due to the rapid advancements in recent years, medical image analysis is largely dominated by deep learning (DL).
Image prediction of disease progression by style-based manifold extrapolation
We present a generic solution for this problem by a methodology that allows the prediction of progression risk and morphology in individuals using a latent extrapolation optimization approach.
