Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...

Single-cell RNA-seq AI analysis has become the default way to make sense of the millions of expression measurements a single experiment can now generate. Turning raw sequencing counts into ...

Electroencephalography (EEG) signals provide a unique opportunity for personal identification due to their inherent permanence and uniqueness. However, EEG data are complex, multidimensional, ...

Abstract: Data-driven soft sensing is widely adopted for real-time quality variable detection due to rapid advancements in machine learning. Industrial process data typically exhibit high ...

Abstract: Effective fault diagnosis for industrial robots is imperative to improve their reliability and availability in safety-critical applications. Proprioceptive signals from servo drive systems ...