Recent advancements in systems biology have been propelled by the increasing power of omics technologies—spanning genomics, transcriptomics, proteomics, ...

However, traditional clinical trial designs are often ill-suited for rare disease research with common challenges including ...

In pet genetics, cancer research, and beyond, Charlie Lieu, MBA ’05, SM ’05, has spent her career harnessing massive data ...

The researchers have developed a new approach to making biometric presentation attack detection (PAD) resistant to demographic bias.

Abstract: Data scarcity remains a crucial bottleneck restricting the performance of infrared small target detection (IRSTD). Especially with the rapid development of the low-altitude economy, IRSTD ...

Achieving high reliability in AI systems—such as autonomous vehicles that stay on course even in snowstorms or medical AI that can diagnose cancer from low-resolution images—depends heavily on model ...

Time series classification is widely used in many fields, but it often suffers from a lack of labeled data. To address this, researchers commonly apply data augmentation techniques that generate ...

ABSTRACT: A degenerative neurological condition called Parkinson disease (PD) that evolves progressively, making detection difficult. A neurologist requires a clear healthcare history from the ...

Abstract: Enhancing the generalization performance of CNN-based deep learning models for network traffic prediction requires a substantial amount of data. However, collecting large-scale network ...