Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.
Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...
No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...
Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...
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 ...
By applying machine learning techniques, engineers at MIT have created a new method for 3D printing metal alloys that produce ...
NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback