We propose using unsupervised clustering of the continuous output of machine learning models to provide discrete risk stratification for predicting time to first treatment in a cohort of patients with ...

A new study used unsupervised machine learning consensus clustering to identify and characterize distinct clusters of those with hospitalized with hyperkalemia.

The core value of unsupervised learning lies in its ability for data-driven exploration, making it particularly suitable for ...

Clustering is an example of unsupervised machine learning, meaning that you do not know ahead of time what groups you are looking for — you want the algorithm to find those groups for you.

Discover how machine learning is helping researchers identify different groups of chronic obstructive pulmonary disease (COPD ...

So instead of fearing machine learning, organizations should learn how to use the technology to the best advantage while also understanding its limitations.

What is unsupervised machine learning? With unsupervised machine learning, a system is like a curious toddler exploring a world they know nothing about.

We propose using unsupervised clustering of the continuous output of machine learning models to provide discrete risk stratification for predicting time to first treatment in a cohort of patients with ...