Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...
You read the “AI-ready SOC pillars” blog, but you still see a lot of this:Bungled AI SOC transitionHow do we do better?Let’s go through all 5 pillars aka readiness dimensions and see what we can ...
Objective: This study aimed to assess the impact of a model shift on ML-based prediction models by evaluating 3 different use cases—delirium, sepsis, and acute kidney injury (AKI)—from 2 hospitals (M ...
Bernice Asantewaa Kyere on modeling that immediately caught my attention. The paper titled “A Critical Examination of Transformational Leadership in Implementing Flipped Classrooms for Mathematics ...
Abstract: With its robust capabilities for non-linear regression and classification, kernel-based learning has emerged as a fundamental component of state-of-the-art machine learning approaches. In ...
Abstract: Digital in-memory compute (IMC) architectures allow for a balance of the high accuracy and precision necessary for many machine learning applications, with high data reuse and parallelism to ...
On some of Ford's newest and most popular pickup trucks, drivers have reported a chilling failure the digital instrument panel suddenly goes dark, leaving them without a speedometer, fuel gauge, or ...
Early identification and prediction of persistent SA-AKI are crucial. Objective: The aim of this study was to develop and validate an interpretable machine learning (ML) model that predicts persistent ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback