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

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

A lab at the University of Idaho will use a Department of Defense grant to develop machine learning models that might be able ...

A University of Idaho lab received $1.3 million from the Department of Defense to study early detection methods for ...

Introduction Accurate preoperative assessment of lymph node metastasis (LNM) is a key determinant of treatment selection in early gastric cancer (EGC), particularly when choosing between endoscopic ...

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

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

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...

Nanoscale device employs magnetic tunnel junctions to convert thermal noise into binary signals for random number generation.

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