High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic ...

Kevin Dayaratna was Director of the Center for Data Analysis and Chief Statistician for Heritage. A variety of statistical tools can detect potential breaches in the integrity of elections. These ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Comprehensive guidelines on the presentation of statistical material in medical/dental journals have been published by Altman et al. elsewhere. 1 The following is a slightly adapted summary of those ...

A relatively simple statistical analysis method can more accurately predict the risk of landslides caused by heavy rain, according to a study coordinated by Brazilian researchers affiliated with the ...

Researchers have developed a machine learning model that could better measure baseball players' and teams' short- and long-term performance, compared to existing statistical analysis methods for the ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...

This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO’s to accelerate their duty of care to develop stronger skills and competencies ...