MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

Find out how machine learning identifies country-specific health system drivers shaping global cancer survival and highlights ...

Researchers developed a machine learning model that could identify children in the ED who were at risk for developing sepsis ...

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Artificial intelligence is quietly transforming how scientists monitor and manage invisible biological pollutants in rivers, ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

APLR builds predictive, interpretable regression and classification models using Automatic Piecewise Linear Regression. It often rivals tree-based methods in predictive accuracy while offering ...

Introduction: Food price volatility continues to be a significant concern in Kenya's economic development, posing challenges to the country's economic stability. Methodology: This study examines the ...