Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Machine learning in drug discovery, along with artificial intelligence, is transforming the pharmaceutical industry by accelerating the development of new treatments. Historically, the process of ...
Experts are increasingly turning to machine learning to predict antibiotic resistance in pathogens. With its help, resistance ...
This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in ...
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 ...
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 ...
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 ...
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...
A new article published in the Journal of Dental Research explores the development of an integrated data-cleaning and subtype discovery pipeline using unsupervised machine learning for comprehensive ...
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, ...
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