In today's scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing ...

Exoplanet science has undergone a profound paradigm shift, evolving from its discovery-driven youth into a data-rich and precision-oriented mature era ...

Machine learning method maps the uncertainty of biodiversity scenarios: The Bigfoot connection ...

How can artificial intelligence improve the analysis of chromatographic data? Artificial intelligence (AI) is a powerful and ...

Continuous learning in artificial intelligence involves a delicate trade-off between forgetting old knowledge and rigidity in ...

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 ...

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The FDA’s new draft guidance on Bayesian methods in clinical trials has been hailed by some as a breakthrough that could speed drug development.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

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...