Search Results for author:
Found 4 papers, 1 papers with code
Robust semi-supervised segmentation with timestep ensembling diffusion models
Medical image segmentation is a challenging task, made more difficult by many datasets' limited size and annotations.
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation
In such settings, semi-supervised learning (SSL) attempts to leverage the abundance of unlabelled data to obtain more robust and reliable models.
Automatic lesion analysis for increased efficiency in outcome prediction of traumatic brain injury
We compare the predictive power of our proposed features to the Marshall score, independently and when paired with classic TBI biomarkers.
MGP-AttTCN: An Interpretable Machine Learning Model for the Prediction of Sepsis
With a mortality rate of 5. 4 million lives worldwide every year and a healthcare cost of more than 16 billion dollars in the USA alone, sepsis is one of the leading causes of hospital mortality and an increasing concern in the ageing western world.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
