Healthcare leaders in North Texas are identifying and addressing maternal health risks early, aiming to improve outcomes in a region with some of the worst maternal health statistics in the country.

Rush uses LeanTaaS' iQueue to analyze data from Epic EHR, enabling predictive scheduling and resource allocation in the OR. The implementation has led to a 12x return on investment, a 5% increase in ...

Spend a few minutes with someone in EMS, fire service, or healthcare, and you’ll likely hear some version of the same concerns: call volumes increasing, crews stretched thin, and many of the systems ...

This project serves as a complete portfolio demonstrating my journey from Python fundamentals to advanced data analytics techniques. It includes hands-on examples of data cleaning, exploration, ...

Can anyone remember their life before artificial intelligence (AI)? Many struggle with that, but what I do remember is how things worked in the business sector, especially in education.

Abstract: Traditional data analytics methods face significant obstacles due to the growing amount of healthcare data from genetic databases, wearable technology, and Electronic Health Records (EHRs).

Imagine a world where artificial intelligence (AI) doesn’t just predict who will win the game but the next play before it happens. My own organization moved toward AI because we found the sector was ...

Silevertinib delivers robust anti-tumor activity as demonstrated by an ORR of 60% and a CNS response rate of 86% in 43 1L NSCLC patients presenting with 35 different non-classical EGFR mutations; no ...

How is AI and data leadership at large organizations being transformed by the accelerating pace of AI adoption? Do these leaders’ mandates need to change? And should overseeing AI and data be viewed ...

Find the best predictive analytics tools to boost customer experience with clear top picks, pricing guidance, and an easy how-to choose checklist. Predictive analytics tools are revolutionizing ...