AI calculations on Mac cluster get big boosts from new RDMA support on Thunderbolt 5

Real-world test of Apple's latest implementation of Mac cluster computing proves it can help AI researchers work using ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...
Nanowerk

Machine Learning model predicts protein binding on gold nanoclusters for biomedicine

A generalizable ML framework predicts protein interactions with ligand-stabilized gold nanoclusters, supporting faster design ...

Machine learning model predicts protein binding on gold nanoclusters

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...
EurekAlert!

Machine Learning Model predict protein binding on gold nanoclusters - Opens doors for next-generation biomedical nanomaterials

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...
ahajournals.org

Abstract 4361575: Phenotyping Cardiogenic Shock Using Unsupervised Machine Learning: A Nationwide Cluster Analysis from National Inpatient Sample

Introduction: Cardiogenic shock (CS) is a heterogeneous clinical syndrome, with varied clinical outcomes driven by hemodynamic states, and initial presentation. However, unsupervised machine learning ...
IEEE

Cluster-Based Machine Learning-Driven Routing for UAV Networks in 6G Environment

Abstract: The sixth generation (6G) wireless networks are envisioned to deliver ultra-low latency, massive connectivity, and high data rates, enabling advanced applications such as autonomous unmaned ...
ascopubs.org

Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
Frontiers

Machine learning consensus clustering for inflammatory subtype analysis in stroke and its impact on mortality risk: a study based on NHANES (1999–2018)

Background: Our study aims to utilize unsupervised machine learning methods to perform inflammation clustering on stroke patients via novel CBC-derived inflammatory indicators (NLR, PLR, NPAR, SII, ...