Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

A machine learning model for prediction of preeclampsia risk using routinely collected data was feasible among pregnancies in ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

The intersection of artificial intelligence and mechanistic neuroscience is rapidly transforming our understanding of neural systems. While AI ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...

However, inconsistent travel times and unpredictable congestion continue to undermine service reliability, particularly in ...