Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.

With peak wildfire season underway in California, PG & E's Chief Meteorologist Scott Stenfel held a virtual Wildfire Season ...

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...

For the first time, mission-focused AI and machine learning capabilities for warfighters have been delivered into the Multi-Domain Mission Support System (MD MSS), marking a significant milestone for ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

Objective: This study aimed to develop and validate an interpretable machine learning model specifically for multiclass hepatic steatosis severity prediction in nonobese individuals to support early ...

Machine learning models narrow down solutions in synthesis, compounding, product design, and more.

Alex Chen's adaptive execution framework, using reinforcement learning, cuts trading costs and improves market visibility.

A steer-by-wire bicycle reliably distinguishes between cornering and unstable riding conditions, enhancing riding safety.

Abstract: As fake news spreads rapidly in social media, attempts to develop detection technology to automatically identify fake news are actively being developed, recently. However, most of them focus ...