This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models like regression, dec ...

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

"The biggest risk is not taking any risk ... the only strategy that is guaranteed to fail is not taking risks," advised Mark Zuckerberg.Every story has a beginning. Every story has an element of risk.

Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...

Diabetic peripheral neuropathy (DPN) is a prevalent and highly disabling complication of diabetes mellitus, associated with markedly increased rates of disability and mortality. Timely intervention ...

ABSTRACT: Microfinance institutions in Kenya play a unique role in promoting financial inclusion, loans, and savings provision, especially to low-income individuals and small-scale entrepreneurs.

Random forest machine learning regression and interactive web application using home loan data to help determine algorithmic discrimination toward race and gender in ...

Abstract: Load forecasting, a crucial aspect of energy management, involves predicting the future electricity demand based on historical data. In the context of monthly time series analysis, this ...