Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
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 ...
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 developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
Researchers at IIT Mandi have developed an advanced real-time landslide monitoring system using machine learning and ...
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