3260 papers • 126 benchmarks • 313 datasets
Predicting medical procedures performed during a hospital admission.
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This work simulates patients at admission time, when decision support can be especially valuable, and proposes *clinical outcome pre-training* to integrate knowledge about patient outcomes from multiple public sources and presents a simple method to incorporate ICD code hierarchy into the models.
A 3D probabilistic segmentation framework augmented with NFs, to enable capturing the distributions of various complexity, and is the first to present a 3D Squared Generalized Energy Distance (D2 GED) of 0.401 and a high 0.468 Hungarian-matched 3D IoU.
The Memory Efficient Video GAN (MeVGAN) is introduced–a Generative Adversarial Network (GAN) that incorporates a plugin-type architecture that utilizes a pre-trained 2D-image GAN to develop specific trajectories within the noise space.
Adding a benchmark result helps the community track progress.