Pursuing computer science (CS) was a no-brainer for Zach Wood-Doughty. A third-generation computer science professor following in his father and grandfather’s footsteps, he was hooked at a very early ...

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 ...

In my last article, I explained how businesses need to differentiate between digital strategy, digitization and digitalization. The piece focused on how everyone uses the terms differently and, ...

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 ...

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...

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, ...

Machine learning is a flexible set of tools for identifying patterns and relationships in complex data and for making decisions based on those data. A machine learning model can allow a vehicle to ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Obstructive sleep apnea syndrome(OSAS) is a very common sleep disorder with high prevalence. Globally, nearly 1 billion adults aged 30 to 69 years, are estimated to ...

Machine learning is becoming increasingly valuable in semiconductor manufacturing, where it is being used to improve yield and throughput. This is especially important in process control, where data ...