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 ...

This paper takes a new look at dam hazard potential classification via machine learning algorithms by proposing a novel geospatial model to estimate new predictors. We take a multi-objective approach ...

Back in the ancient days of machine learning, before you could use large language models (LLMs) as foundations for tuned models, you essentially had to train every possible machine learning model on ...