A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...
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 ...
14d
A machine learning model may enable liver cancer risk prediction with routine clinical information
A machine learning model that analyzes patient demographics, electronic health record data, and routine blood test results ...
Sepsis is one of the most common and lethal syndromes encountered in intensive care units (ICUs), and acute respiratory ...
NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...
Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...
The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...
Climate Compass on MSN
The science behind earthquake prediction efforts
Every year, the Earth shakes thousands of times. Most of those tremors go unnoticed, felt only by sensitive instruments ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results