Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

Researchers from King Abdullah University of Science and Technology (KAUST) have developed deepBlastoid, the first deep-learning platform ...

Researchers say the deep learning model may help to create leads for new cancer diagnostics, patient stratification, and future therapies.

Machine learning models showed roughly 40% improvement in diagnostic accuracy compared tostandard oral food challenges, skin prick tests, and ...

Retinal detachments can be diagnosed using a deep learning-powered fundus imaging system, offering expertise to screening sites.

Membership Inference Authors, Creators & Presenters: Zitao Chen (University of British Columbia), Karthik Pattabiraman ...

With the rapid development of electric vehicles and energy storage systems (ESSs), accurate state-of-health (SOH) estimation for lithium-ion batteries has become crucial for ensuring safety and ...