Support vector machines lead machine learning models in predicting liver decompensation

LONDON — Support vector machines had the highest accuracy in predicting liver decompensation among a subset of patients in Germany compared with other machine learning models, according to data presented at the International Liver Congress.“Since decompensation of cirrhosis significantly increases mortality, early detection of patients at risk of worsening liver function is of paramount importance,” Sophie Elisabeth Müller, of Saarland University Medical Center in Homburg, Germany, and colleagues wrote.Seeking to identify predictors of hepatic decompensation, MüllerRead More