Endoscopy-based deep learning algorithms demonstrate higher sensitivity and specificity than endoscopists overall in detecting early esophageal squamous cell carcinoma.

Researchers have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions our DNA, which make up the vast majority of the human genome.

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...

Assessing mortality trends among patients with lip and oral cavity cancer due to tobacco consumption: A systematic analysis of the Global Burden of Disease-2021.

Compare deep learning cell segmentation tools Cellpose and StarDist: how each works, how they differ by imaging type, and ...

A new study published in PNAS Nexus by researchers at Carnegie Mellon University (CMU) demonstrates how a noninvasive brain-computer interface (BCI) powered by artificial intelligence (AI) deep ...

The U.S. Deep Learning Market is Projected to Grow from $37.14 Billion in 2025 to $596.02 Billion by 2035, While Europe is ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

“A deep learning device be trained on a specific subset of data is incident to the very nature of machine learning.” – Federal Circuit The U.S. Court of Appeals for the Federal Circuit (CAFC) issued a ...