In many public healthcare systems, particularly in resource-constrained environments, time-series forecasting models offer a practical, interpretable, and evidence-based alternative (Stacey et al., ...

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...

Celldetective is an open-source software integrating segmentation, tracking, and event detection to perform high-throughput end-to-end study of dynamic cell interactions, without requiring coding ...

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...

Stewart Brand, an American author, once said, “Once a new technology rolls over you, if you are not the part of the steamroller, you are ‌part of the road” ...

Large language models (LLMs) such as ChatGPT, Claude Cowork and GitHub Copilot have revolutionised the way individuals and organizations interact with artificial intelligence for content generation, ...

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...

The classification of dry bean varieties is vital for agricultural productivity and food quality control. However, the inherent class imbalance in datasets poses challenges for machine learning (ML) ...

Abstract: The article deals with comparative analysis of SQL and NoSQL embedded databases performance on single-board computer systems, such as SQLite, LMDB and UnQLite. The aim of the article is to ...

Funding mechanisms impact the cost effectiveness of the science conducted, as extramural NIH grants to universities excel at producing papers and citations, while intramural NIH hiring more ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...