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Machine learning models to predict disease progression among veterans with hepatitis C virus.

Monica A KonermanLauren A BesteTony VanBoang LiuXuefei ZhangJi ZhuSameer D SainiGrace L SuBrahmajee K NallamothuGeorge N IoannouAkbar K Waljee
Published in: PloS one (2019)
Boosted-survival-tree based models using longitudinal information are statistically superior to cross-sectional or linear models for predicting development of cirrhosis in CHC, though all four models were highly accurate. Similar statistical methods could be applied to predict outcomes in other non-linear chronic disease states.
Keyphrases
  • hepatitis c virus
  • cross sectional
  • machine learning
  • human immunodeficiency virus
  • healthcare
  • insulin resistance
  • metabolic syndrome
  • deep learning
  • social media