Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

Advances in artificial intelligence (AI) are now opening new possibilities for faster and more accurate flood mapping, ...

A machine learning-driven framework accurately predicts MPA exposure and supports individualized dosing in childhood-onset LN.

Read more about AI and machine learning drive digital transformation across global mining operations on Devdiscourse ...

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

Balancing nitrogen use is critical for maximizing crop yield while minimizing environmental and economic costs.

RESEARCHERS reported that new transcranial magnetic stimulation (TMS) biomarkers, combined with machine learning, accurately distinguished individuals with major depressive disorder (MDD) from healthy ...

ABSTRACT: The surge of digital data in tourism, finance and consumer markets demands predictive models capable of handling volatility, nonlinear dynamics, and long-term dependencies, where traditional ...

Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...

Abstract: Deep learning methods have been widely employed to diagnose faults in power converters. However, it is challenging to diagnose multiple faults in two-stage charging power modules. Besides, ...

Nanotechnology and machine learning are transforming energy systems by enhancing engine efficiency and sustainability. The integration of advanced nanomaterials, such as gold nanoparticles (AuNPs), ...

Acute ischemic stroke (AIS) patients often experience poor functional outcomes post-intravenous thrombolysis (IVT). Novel computational methods leveraging machine learning (ML) architectures ...