Nature

Deep embedded clustering generalisability and adaptation for integrating mixed datatypes: two critical care cohorts

We validated a Deep Embedded Clustering (DEC) model and its adaptation for integrating mixed datatypes (in this study, numerical and categorical variables). Deep Embedded Clustering (DEC) is a ...
Nature

Neural network-based clustering model of ischemic stroke patients with a maximally distinct distribution of 1-year vascular outcomes

Clustering stroke patients with similar characteristics to predict subsequent vascular outcome events is critical. This study aimed to compare several clustering methods, particularly a deep neural ...
Semiconductor Engineering

Transformer Model Based Clustering Methodology For Standard Cell Layout Automation (Nvidia)

A new technical paper titled “Novel Transformer Model Based Clustering Method for Standard Cell Design Automation” was published by researchers at Nvidia. “Standard cells are essential components of ...
ascopubs.org

Clinical Validity of a Prognostic Gene Expression Cluster-Based Model in Human Papillomavirus–Positive Oropharyngeal Carcinoma

Association of 17q22 Amplicon Via Cell-Free DNA With Platinum Chemotherapy Response in Metastatic Triple-Negative Breast Cancer Patients with HPV DNA-positive OPCs with locoregionally advanced ...
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 ...
Visual Studio Magazine

Data Clustering Using a Self-Organizing Map (SOM) with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on technique for visualizing and clustering data. A self-organizing map (SOM) is a data structure that can be used ...