Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

shinyOPTIK, a User-Friendly R Shiny Application for Visualizing Cancer Risk Factors and Mortality Across the University of Kansas Cancer Center Catchment Area We trained and validated two-phase ML ...

Artificial intelligence changed how decisions are made. Quantum computing will decide whether those decisions remain secure.

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

We developed two algorithms to identify patients with stomach, lung, colorectal, breast, and cervical cancers: diagnosis only (algorithm 1), and combining diagnosis, treatments, and medicines ...

The Foundations of Data Structures and Algorithms specialization includes two optional preparation courses and a three-course pathway to earn admission to the Online MS in Computer Science. You must ...