Devdiscourse

Self-supervised AI can unlock hidden disease patterns

Published as an arXiv preprint, the paper details how unsupervised and self-supervised AI models are matching or surpassing ...
IEEE

Unsupervised Domain Adaptation for Medical Image Segmentation by Disentanglement Learning and Self-Training

Abstract: Unsupervised domain adaption (UDA), which aims to enhance the segmentation performance of deep models on unlabeled data, has recently drawn much attention. In this paper, we propose a novel ...
IEEE

Unsupervised Brain Lesion Segmentation Using Posterior Distributions Learned by Subspace-Based Generative Model

Abstract: Unsupervised brain lesion segmentation, focusing on learning normative distributions from images of healthy subjects, are less dependent on lesion-labeled data, thus exhibiting better ...
News Medical

New AI model performs medical image segmentation with far less data

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...
Scientific Research Publishing

Engl, E., Smittenaar, P. and Sgaier, S.K. (2019) Identifying Population Segments for Effective Intervention Design and Targeting Using Unsupervised Machine Learning: An End-to ...

ABSTRACT: Doping is an issue associated with elite sports as athletes attempt to enhance their performance to gain an edge over other athletes. However, the prevalence of doping is continuously ...