A resilient data strategy must treat unstructured content not as archival noise but as a primary input into the enterprise ...

With so much attention devoted to the purported wonders of predictive cognitive computing models (typically characterized by classic machine learning and deep learning), it’s easy to lose sight of the ...

The efficient management of hospital resources, particularly in terms of bed utilisation and staff allocation, is increasingly critical in modern healthcare systems. Predictive modelling for hospital ...

Why Data Matters for AI Poor data quality and fragmented identity undermine predictive performance. TransUnion’s identity graph and enrichment capabilities provide the single source of truth AI ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to unravel the complexity of ...

Artificial intelligence (AI) tools are revolutionizing the way entire industries operate. The potential scope of AI is firmly in our public consciousness, whether through scare stories about the ...

Theoretical and simulation estimates of turbulent transport (high-dimensional data that depend on plasma conditions such as density, temperature, and magnetic field) are used as low-fidelity data, and ...

Predictive modeling technology is capable of sifting through massive data sets and uncovering the patterns and trends that correlate the target data elements to some outcome(s) of interest. Paul ...

With the addition of Scytec’s DataXchange software, Minitab extends its capabilities to collect comprehensive, real-time operational data from machines such as CNC (Computer Numerical Control) ...