Cardiovascular diseases remain a leading cause of mortality globally, driving the need for more precise diagnostic and predictive tools. Traditional ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.

Abstract: A goal for the validation of computational electromagnetics (CEM) is to provide the community with a simple computational method that can be used to predict the assessment of electromagnetic ...

Structural biology has long been a leader in open data culture; the Protein Data Bank (PDB), Electron Microscopy Data Bank (EMDB), and Biological Magnetic ...

New machine learning framework predicts promising nucleoside hydrogels before they are synthesized and tested in the ...

Validate AI-generated insights, establish governance, and prioritize real-world research where it delivers the greatest value ...

Abstract: As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in ...

Scientific research has never produced more information than it does today. Across nearly every discipline, researchers face ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Synthetic data is a vital substitute for real sensitive personal data in supporting social science research and policy ...

Recent industry announcements highlight a shift towards integrated, scalable cooling solutions driven by AI and HPC demands.

The increasing globalization of drug development programs has driven a growing need for rigorous cross-validation of bioanalytical assays across multiple laboratory sites. As bioanalytical methods ...