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Found 5 papers, 1 papers with code
Deep Semi-Supervised Embedded Clustering (DSEC) for Stratification of Heart Failure Patients
In this work we apply deep semi-supervised embedded clustering to determine data-driven patient subgroups of heart failure from the electronic health records of 4, 487 heart failure and control patients.
Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units
The proposed approach is compared to a standard clinical risk predictor (QRISK) and machine learning alternatives using 5-year data from a NHS Foundation Trust.
Extracting 3D Vascular Structures from Microscopy Images using Convolutional Recurrent Networks
Vasculature is known to be of key biological significance, especially in the study of cancer.
maskSLIC: Regional Superpixel Generation with Application to Local Pathology Characterisation in Medical Images
Supervoxel methods such as Simple Linear Iterative Clustering (SLIC) are an effective technique for partitioning an image or volume into locally similar regions, and are a common building block for the development of detection, segmentation and analysis methods.
Pieces-of-parts for supervoxel segmentation with global context: Application to DCE-MRI tumour delineation
Rectal tumour segmentation in dynamic contrast-enhanced MRI (DCE-MRI) is a challenging task, and an automated and consistent method would be highly desirable to improve the modelling and prediction of patient outcomes from tissue contrast enhancement characteristics - particularly in routine clinical practice.
