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 ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Feature engineering involves systematically transforming raw data into meaningful and informative features (predictors). It is an indispensable process in machine learning and data science. This ...