Machine learning has become the critical enabler for addressing these challenges. Traditional ML models, including random ...

A new study combining multiomics approaches with machine learning has identified plasma protein changes that may allow for ...

Researchers have identified multiple causal biomarkers for metabolic dysfunction-associated steatotic liver disease (MASLD), ...

Traditional machine learning methods like Support Vector Machines, Random Forest, and gradient boosting have shown strong ...

A new study applying multi-omics techniques and machine learning identified 33 plasma proteins that differ significantly in ...

A study in the International Journal of Critical Infrastructures discusses a financial early warning system based on an ...

A pioneering study published in the International Journal of Advanced Artificial Intelligence Research, authored by Olabayoji Oluwatofunmi Oladepo and Opeyemi Eebru Alao of Swansea University, has ...

A machine learning–based tool accurately predicted risk for recurrent inflammatory activity after DMT discontinuation in MS, highlighting its potential to guide personalized treatment decisions.

Sodium-ion batteries (SIBs) emerge as a key option for next-generation electrochemical energy storage, thanks to abundant sodium resources, ...

Researchers have developed a machine learning approach that can optimize the treatment of livestock manure and predict how ...