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, ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in complex two-dimensional (2D) data, with potential applications ranging from ...

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 ...

Artificial intelligence has become a popular tool for job recruiters, in part because programmers can code applicant-screening algorithms to avoid any explicit discrimination in their decision-making ...

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 ...

There's a saying that a messy kitchen is a happy kitchen. However, that concept doesn't apply to data processing. Artificial intelligence (AI) and machine learning (ML) can't properly execute without ...

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 ...

Through data, algorithms communicate with their environments and get to “know about” and “learn from” what is happening around them. Algorithms without living data are no more than sheer mathematical ...

Artificial intelligence can be a beautiful thing for business, with a lot of promise. But this promise has yet to deliver tangible results. Many AI projects fail in various stages of experimentation ...