A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD than traditional tools. Heart failure is one of the most serious and ...

FraudGuard AI is a machine learning-based web application developed to detect suspicious and fraudulent transactions. The system uses a trained ML model along with rule-based checks to classify ...

Enterprise software is undergoing a major transformation as machine learning becomes deeply embedded into core digital products. Organizations are no longer using ML only for experimental analytics; ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

This paper presents a machine learning–based nowcasting framework for estimating quarterly non-oil GDP growth in the Gulf Cooperation Council (GCC) countries. Leveraging machine learning models ...

The delayed coker unit (DCU) at TotalEnergies’ Port Arthur refinery's is a complex system that thermally cracks heavy residual oils into lighter, more valuable oil products and petroleum coke. As ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

knitr::opts_chunk$set(echo = TRUE, warning=FALSE, message=FALSE, fig.width=10, fig.height=5) options(width=120) library(lattice) library(ggplot2) library(plyr ...