If data used to train artificial intelligence models for medical applications, such as hospitals across the Greater Toronto ...

Snowflake is addressing the complexity of migrating legacy data systems into the Snowflake ecosystem with SnowConvert AI, a ...

Understanding how cities grow is vital for shaping sustainable urban futures—but mapping the true extent of urban expansion ...

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes means ...

Test cases are standard means to ensure the correctness of data flows in smart contracts. To more efficiently generate test cases with high coverage, we propose an improved genetic algorithm-based ...

Artificial intelligence and robotics are revolutionizing drug discovery by automating laboratory processes and enabling rapid ...

The use of these techniques generates a dataset for measuring the accuracy of diabetes status prediction. The Neural Networks algorithm achieves an accuracy rate of 79.65%, the SVM algorithm 83.69%, ...

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 ...

aArtificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA bDepartment of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer ...

This study aims to develop a model based on a machine learning algorithm that can predict the risk of in ... and early intervention in this high-risk cohort. Figure 1. Flow chart of the study. AMI, ...