Shift verification effort from a single, time-consuming flat run to a more efficient, distributed, and scalable process.
BhGLM is a freely available R package that implements Bayesian hierarchical modeling for high-dimensional clinical and genomic data. It consists of functions for setting up various Bayesian ...
Currently hierarchical data models (HDM) must be generated with the same EDA tool that customers will use to consume the HDM ...
The TRM takes a different approach. Jolicoeur-Martineau was inspired by a technique known as the hierarchical reasoning model ...
This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual ...
Bayesian hierarchical modeling is a popular approach to capturing unobserved heterogeneity across individual units. However, standard estimation methods such as Markov chain Monte Carlo (MCMC) can be ...
Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
There were modest reductions in cognitive performance seen for longer fasting intervals and for younger vs older participants during fasts.
Microcredentials operate differently from traditional education, and they call for a more flexible, adaptable system to ...
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