IEEE

DCGMDL: Deep Conditional Generative Model for Dictionary Learning in Supervised Classification

Abstract: In this paper, we propose the DCGMDL model, which utilizes a feed-forward neural network to exploit the inherent nonlinearity of data for dictionary learning. Unlike traditional dictionary ...
IEEE

High Quality Dynamic Occlusion Computational Ghost Imaging Guided Through Conditional Diffusion Model

Abstract: High-quality imaging under low sampling is the key to the practical application of computational ghost imaging, and significant progress has been made. However, as far as we know, most ...
The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...