Python Physics: Create a Linear Regression Function using VPython! 🐍📈 In this video, we’ll guide you through creating a simple linear regression function to analyze data, visualizing the results ...

ABSTRACT: This study examined the relationship between the Monetary Policy Rate (MPR) and inflation across five continents from 2014 to 2023 using both Frequentist and Bayesian Linear Mixed Models ...

Different AI models win at images, coding, and research. App integrations often add costly AI subscription layers. Obsessing over model version matters less than workflow. The pace of change in the ...

The CMS Innovation Center has debuted a new model to encourage the use of technology to treat chronic diseases, which could be a boon for health tech companies that have struggled with reimbursement.

Oregon Attorney General Dan Rayfield and district attorneys of the state’s three largest counties say they will start investigating and prosecuting federal immigration enforcement agents if they don’t ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Computer-use agents have been limited to primitives. They click, they type, they scroll. Long action chains amplify grounding errors and waste steps. Apple Researchers introduce UltraCUA, a foundation ...

Neurointervention is a highly specialized area of medicine and, as such, neurointerventional research studies are often more challenging to conduct, require large, multicenter efforts and longer study ...

Medal, a platform for uploading and sharing video game clips, has spun out a new frontier AI research lab that’s using its trove of gaming videos to train and build foundation models and AI agents ...

In microbiome studies, addressing the unique characteristics of sequence data—such as compositionality, zero inflation, overdispersion, high dimensionality, and non-normality—is crucial for accurate ...

Abstract: For a relatively small labeled dataset from high-dimensional generalized linear models with block-wise missing covariates and a large unlabeled dataset, we utilize a model-assisted approach ...