For four years, NASA’s planet-hunting telescope photographed the light of 2.2 million stars. The data sat in public archives, ...

Abstract: Healthcare operations management faces unprecedented challenges in resource allocation, patient flow optimization, and clinical decision-making under uncertainty. This paper presents a ...

Abstract: Hyperparameter tuning is a crucial step in the development of machine learning models, as it directly impacts their performance and generalization ability. Traditional methods for ...

Combining dogs' powerful sense of smell with advanced analytics, researchers are testing a non-invasive method to detect ...

Artificial intelligence is accelerating the design of microfluidic devices, replacing months of manual iteration with rapid, data-driven optimization. Techniques like Bayesian optimization and machine ...

Now, artificial intelligence (AI) tools are providing powerful new ways to address long-standing problems in physics. “The ...

GOES-East satellite observations and machine learning have, for the first time, connected this observed structure to the much ...

The future of conflict prediction relies on combining technical ability, institutional governance and ethical responsibility.

Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...

The FDA’s new draft guidance on Bayesian methods in clinical trials has been hailed by some as a breakthrough that could speed drug development. But statisticians and researchers are divided on ...

Traditional QSRR models are limited to single-column predictions, hindering adaptability across diverse LC setups in pharmaceutical settings. The new ML-based approach predicts retention times using ...