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 ...

Supervised machine learning improves predictions of compressive strength in industrial waste-modified concrete, supporting ...

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 ...

Background Multiple clinical risk scores have been developed for acute upper gastrointestinal bleeding (AUGIB) with limited sensitivity and specificity. We aim to develop a machine learning model to ...

aInstitute of Computer-Assisted Cardiovascular Medicine, Deutsches Herzzentrum der Charité Augustenburger Platz 1, 13353 Berlin, Germany bDepartment of Congenital Heart Disease – Pediatric Cardiology, ...

Coastal and nearshore zones face growing pressure from storms, flooding, erosion, and sea-level rise, which threaten civil infrastructure such as ports, ...

With the increased need for data to support artificial intelligence (AI) and large language models, data aggregation and de-identification are ...

Executives are making significant investment decisions based on AI outcomes they cannot independently verify. A machine ...

AI model suggests deep vein thrombosis may be identified more accurately using gut microbiome profiles. Read more.

Scientific research has never produced more information than it does today. Across nearly every discipline, researchers face ...

Five students partnered with Dr. Ahmad Ghafarian, a UNG professor of computer science and cybersecurity, on the application ...

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 ...