Pietro Rossi had a problem. An insurance company needed a model that could price bonds based on the likelihood of changes in credit ratings. The standard, off-the-shelf models are based on probability ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Subvisible particle testing addresses regulatory limits for particulate matter in parenteral drugs, ophthalmic solutions, and lipid emulsions.

Leaks and Obstructions: Troubleshooting Common Problems Close to the Point of Sample Injection ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

Abstract: Traditional single-center learning algorithms often face significant limitations in handling heterogeneous data integration, including insufficient generalization ability, weak privacy ...

Quantum Machines, a provider of advanced hybrid quantum-classical control solutions, announced today the release of Qualibrate (which the company spells QUAlibrate), an open-source framework for ...

The graph leverages QUAlibrate's parallel calibration capabilities to dramatically reduce calibration times. Looking ahead, Quantum Machines and NVIDIA are developing software libraries that will ...

Knowledge graphs are reshaping how we organize and make sense of information. By connecting data points and revealing relationships between them, these powerful tools are transforming industries, from ...