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 ...

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 ...

"Medical Genomics" research group at ISTA "Data Science, Machine Learning, and Information Theory" research group at ISTA Al Depope, Jakub Bajzik, Marco Mondelli, and Matthew R. Robinson. 2026. Joint ...

RnD® platform connects targets, compounds and authenticated human cell models to reduce manual searching and enable ...

Data collection and analysis in solar PV installations is increasingly sophisticated, particularly relating to grid ...

A fundamental divide between data engineering and business analytics complicates how organizations operate in a rapidly evolving digital environment. Enterprises manage unprecedented volumes of ...

There's been a seismic shift in science, with scientists developing new AI tools and applying AI to just about any question that can be asked. Researchers are now putting actual seismic waves to work, ...

A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on ...

Image Marina Sirota, PhD, in her lab at UCSF Mission Bay. Sirota and her team used AI to analyze pregnancy data, enabling a master's student and a ...

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...

For retailers and investors, the message is that consumers are still in the game—they’re just demanding a clearer value ...