Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
This prediction approach achieves higher agreement in predictions by optimizing the concordance correlation coefficient (CCC), which measures how well pairs of observations fall on the 45-degree line ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...
We’re living in a time when data shapes almost every choice we make, from picking a winning football team to deciding where ...
An international team of mathematicians, led by Lehigh statistician Taeho Kim, has introduced an innovative method that could significantly improve how scientists make predictions, especially in ...