Williams, A. and Louis, L. (2026) Cumulative Link Modeling of Ordinal Outcomes in the National Health Interview Survey Data: Application to Depressive Symptom Severity. Journal of Data Analysis and ...

Corporate leaders are racing to hire artificial intelligence talent, convinced that a few high-profile specialists can ...

Abstract: The utilization of incremental models is a straightforward and effective method to improve the robustness of model predictive control (MPC). However, there ...

During model development, it is essential to focus on model quality, including reducing bias risk, designing appropriate sample sizes, conducting external validation, and ensuring model ...

Chad Beam provides the ins and outs of the implementation of GIS, advanced communication systems and predictive modeling to ensure that staffing, to whatever extent, is utilized most effectively. A ...

A predictive model identifies RA patients at risk of D2T-RA, using machine learning and real-world data for early intervention. Patient-reported outcomes, such as pain and fatigue, are stronger ...

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 ...

Dr. Bin Tang, Founder & CEO of Noah Digital, is an internationally recognized AI & digital marketing leader & author of “Local to Global.” For years, digital marketing has been synonymous with ...

A machine learning web application that predicts resale flat prices in Singapore using historical HDB data. Built with Scikit-learn and Streamlit, the app helps buyers and sellers estimate market ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...