In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

Objective: This study compared a conventional logistic regression model with machine learning (ML) models using demographic and clinical data to predict outcomes at 2 and 6 months of treatment for MDR ...

Discovering effective drug combinations may now be easier thanks to a screening platform made public today by St. Jude Children's Research Hospital scientists. Many diseases, including cancers, ...

(L) First and co-corresponding author Charlie Wright, PhD, St. and (R) co-corresponding author Paul Geeleher, PhD, both of the St. Jude Department of Computational Biology. (MEMPHIS, Tenn. – December ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

ABSTRACT: Bipolar disorder is a complex psychiatric condition characterized by high variability in treatment response, posing a major challenge for clinicians striving to personalize care. Traditional ...

Abstract: In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in social ...

LCGC International interviewed Bob Pirok from the University of Amsterdam, Netherlands to discuss strategies for enhancing method robustness in 2D LC, practical approaches for tracking peaks across ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...