Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

A research team has mapped how machine learning is transforming the global tea industry, revealing that data-driven technologies now enhance tea cultivation, harvesting, processing, and quality ...

A key challenge arises from agricultural data itself. Crop environments are highly variable, influenced by local climate, ...

Public health officials have long struggled to see outbreaks coming before hospitals fill up. Now a new generation of machine ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

Hitchcock and Pande will advise on the continued development and scaling of insitro's AI-driven ChemML™ platform as it is deployed across insitro's pipeline and partner programs. Their guidance will ...

New approaches hurdle biological barriers to attack recalcitrant targets to tackle difficult-to-treat and recurrent cancers.

This important study describes a deep learning framework that analyzes single-cell RNA data to identify a tumor-agnostic gene signature associated with brain metastases. The identified signature ...

For the scientific enterprise, 2025 was marked by setbacks and challenges. But scientists are no strangers to adversity—the ability to overcome obstacles is built into our training. In turn, research ...

Sebastian Marquez ’16, MA ’19, Ph.D. ’20 honed research skills at the College of Engineering & Computing and cultivated ...