Topological Data Analysis (TDA) is an innovative framework that utilises principles from algebraic topology to extract intrinsic patterns and structural features from complex, multi‐dimensional data.

A challenging trend is happening in the Big Data industry, many data sets are increasingly foreign in terms of the data analysis tools available to extract intelligence from them. It isn’t the size of ...

Topological Data Analysis (TDA) is an increasingly influential framework that leverages the principles of algebraic topology to extract, quantify and visualise the intrinsic structure of complex, high ...

The talk below, “Topological Data Analysis for the Working Data Scientist” was presented at the SF Data Mining meetup group. Speaker Anthony Bak begins with a short review of the Mapper algorithm and ...

Researchers used topological data analysis to improve the predictions of physical properties of amorphous materials by machine-learning algorithms. This may allow for cheaper and faster calculations ...

Epidemiology of MET gene mRNA expression in metastatic colorectal cancer: Analyses of a real-world clinicogenomic database. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This ...

Image: Ralph Losey with AI. [EDRM Editor’s Note: EDRM is proud to publish Ralph Losey’s advocacy and analysis. The opinions and positions are Ralph Losey’s copyrighted work. All images in the article ...