DisPred is a deep-learning-based framework that can integrate data from diverse populations to improve the generalizability of genetic risk prediction. It combines a disentangling…
Browsing: Autoencoder
This article presents a novel approach to unsupervised recognition and segmentation of lesion images, using the framework of fast data density functional transform (fDDFT).…
This article presents a framework designed to support the analysis and assessment of neonatal MRI brain scans, which can be used as an aid…