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

Abstract: Ovarian cancer remains one of the most difficult gynecological cancers to detect early, often resulting in poor survival rates. This study presents a comparative analysis of machine learning ...

Japanese researchers develop an adaptive robot motion system that enables human-like grasping using minimal training data.

Despite rapid robotic automation advancements, most systems struggle to adapt their pre-trained movements to dynamic ...

As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become increasingly ...

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.

Machine learning models reveal that histone marks are predictive of gene expression across human cell types and highlight important nuances between natural control and the effects of CRISPR-Cas9-based ...

Four Oxford University academics have been honoured in the Royal Astronomical Society (RAS)'s 2026 Awards , announced today. Each year the RAS Awards ...

That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...

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

A new study published in the journal of BMC Nephrology revealed that a U-shaped link between high stress hyperglycemia ratio ...