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

Machine learning algorithms can predict which candidates are more likely to succeed in a given role by analyzing past hiring ...

See how machine learning is spotting Alzheimer’s years before symptoms begin—using brain scans to help guide earlier, more ...

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

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

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Background: Pancreatic cancer (PC) is highly refractory to most treatments. Multimodal treatment, combining several types of therapies, is likely to benefit PC patients. However, it remains unclear ...

Background: Liver failure is associated with high short-term mortality, and the predictive value of clinical factors for patients undergoing artificial liver therapy is uncertain. We aim to develop ...

1 School of Taxation and Public Administration, Shanghai Lixin University of Accounting and Finance, Shanghai, China. 2 School of Business, Computing and Social Sciences, University of Gloucestershire ...

What if the key to unlocking faster, more efficient machine learning workflows lies not in your algorithms but in the hardware powering them? In the world of GPUs, where raw computational power meets ...