Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Geospatial Information Systems (GIS) have transformed the way we capture, store, and analyse spatial data by integrating methods from computer science, statistics and geography. Central to GIS is the ...

This is where AI-augmented data quality engineering emerges. It shifts data quality from deterministic, Boolean checks to ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

How to Improve Cancer Patients ENrollment in Clinical Trials From rEal-Life Databases Using the Observational Medical Outcomes Partnership Oncology Extension: Results of the PENELOPE Initiative in ...

Outside of tightly controlled environments, most robotic systems still struggle with reliability, generalization and cost. The gap between what we can demonstrate and what we can operate at scale ...