Safe Pro Awarded New $1.3 Million U.S. Government Subcontract to Integrate Real-Time AI Landmine Detection into Unmanned Ground Vehicles

Under the award from a leading U.S. Defense Prime Contractor, Forterra, Safe Pro will integrate and test its proprietary advanced computer vision and machine learning AI pipeline onboard autonomous ...
AHA/ASA Journals

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
emjreviews.com

Editor’s Pick: Recent Advances in Understanding the Endophenotypes of Osteoarthritis

Osteoarthritis, like many other common diseases, is not a single disease entity but has several different endotypes, which differ by pathophysiologic pathway, cytokine pattern, and mechanism of ...

UPDATE: Safe Pro Awarded U.S. Army Order For AI-Powered Threat Analysis Kit Together with Red Cat Black Widow Drones

Detailed price information for Red Cat Holdings Inc (RCAT-Q) from The Globe and Mail including charting and trades.
LinkedIn

Clustering in Machine Learning: Types, Algorithms & Key Methods Explained

Clustering stands as one of the foundational concepts in machine learning. It enables systems to automatically organize similar data points into meaningful groups — all without requiring labeled ...
BizTech

What Are the Benefits of Unsupervised Machine Learning and Clustering?

Nathan Eddy works as an independent filmmaker and journalist based in Berlin, specializing in architecture, business technology and healthcare IT. He is a graduate of Northwestern University’s Medill ...
Nature

Clustering and machine learning techniques identify air pollution regimes in Greater Cairo

Air pollution poses a severe and persistent environmental and public health challenge in Greater Cairo, where concentrations of fine particulate matter (PMâ‚‚.â‚…) regularly exceed World Health ...
Frontiers

A graph clustering algorithm with hypergraph learning and a core-attachment strategy for protein complex identification

Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...
Frontiers

Uncovering distinct clinical phenotypes in disseminated intravascular coagulation through machine learning-enabled cluster analysis

Disseminated intravascular coagulation (DIC) is a critical condition encountered in the intensive care unit (ICU), characterized by multiple etiologies and variable outcomes. Distinguishing between ...
Nature

Unbiased clustering of acute-on-chronic liver failure patients using machine learning in a real-world ICU cohort

Acute-on-chronic liver failure is a complex condition with varied definitions, complicating risk stratification and targeted management. We apply unsupervised clustering to data from 1,256 patients ...