A novel image-based deep learning approach achieves high accuracy and interpretability, offering potential for clinical ...

Dr. Abolfazl Karimpour, Assistant Professor of Transportation Engineering at SUNY Polytechnic Institute and Director of the ...

In the Age of AI, many health care providers dream of a digital assistant, unencumbered by fatigue, workload, burnout or ...

The idea of open versus closed (or proprietary) models is familiar to anyone who has worked in software, and the definition ...

Fractured and incomplete datasets are a key barrier towards effectively training AI models for deployment in healthcare ...

Companies become so good at generating perfect fake customers that they stop talking to real ones. The models work great until they meet actual humans.

Why Data Modeling is Still Relevant If you're wondering whether data modeling is still relevant in today's fast-paced, data-driven world, this white paper is for you. You'll discover how data modeling ...

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 ...

Using PowerPivot for Data Modeling When you use PowerPivot, you can import millions of rows of data from various sources such as databases, spreadsheets, and online services. This capability is ...

The PRISSMM™ cancer data modeling system, enhanced by and licensed from Memorial Sloan Kettering Cancer Center (MSK), is a state-of-the-art data modeling system that allows users to curate clinical ...