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Found 5 papers, 1 papers with code
Cross-adversarial local distribution regularization for semi-supervised medical image segmentation
Medical semi-supervised segmentation is a technique where a model is trained to segment objects of interest in medical images with limited annotated data.
Estimation of Clinical Workload and Patient Activity using Deep Learning and Optical Flow
Contactless monitoring using thermal imaging has become increasingly proposed to monitor patient deterioration in hospital, most recently to detect fevers and infections during the COVID-19 pandemic.
Deep EHR Spotlight: a Framework and Mechanism to Highlight Events in Electronic Health Records for Explainable Predictions
The wide adoption of Electronic Health Records (EHR) has resulted in large amounts of clinical data becoming available, which promises to support service delivery and advance clinical and informatics research.
MED-TEX: Transferring and Explaining Knowledge with Less Data from Pretrained Medical Imaging Models
To interpret the teacher model and assist the learning of the student, an explainer module is introduced to highlight the regions of an input that are important for the predictions of the teacher model.
Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss
In this paper, we propose a novel deep learning-based generative adversarial model, RefineGAN, for fast and accurate CS-MRI reconstruction.
