Prediction-powered inference integrates a small gold-standard dataset with a large auxiliary dataset informed by machine ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...

Pancreatic cancer mortality trends (2018-2023): Exposing racial inequities in Michigan's cancer burden. AUC for the PurIST baseline, the top 2 unimodal models, and the best fusion model for each ...

Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...

As agent hype fades, machine learning quietly proves it’s still essential.

During the last few years or so more people have been been jumping on the artificial intelligence bandwagon and talking about its potential influence on the planet as a whole. The world is much closer ...