Why has machine learning become so vital in cybersecurity? This article answers that and explores several challenges that are inherent when applying machine learning. Machine learning (ML) is a ...

And they're trying to remedy a related problem, too: the lack of resources that teach "how" to use machine learning to detect antibiotic resistance. In a paper in PLOS Computational Biology, the SFSU ...

To determine correlation of inter reader variability in sum of diameters using RECIST 1.1 with end point assessment in lung cancer. A systematic evaluation of models predicting short-term mortality ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Researchers are applying artificial intelligence and other techniques in the quest to forecast quakes in time to help people find safety. In September 2017, about two minutes before a magnitude 8.2 ...

Experts at the Table: Semiconductor Engineering sat down to discuss how increasing complexity in semiconductor and packaging technology is driving shifts in failure analysis methods, with Frank Chen, ...

In the field of experimental solid mechanics – a discipline that focuses on understanding and measuring the physical properties of different materials – researchers have traditionally relied on ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...