Machine learning using longitudinal prescription and medical claims for the detection of nonalcoholic steatohepatitis (NASH)

Autor: Yasar, Ozge, Long, Patrick, Harder, Brett, Marshall, Hanna, Bhasin, Sanjay, Lee, Suyin, Delegge, Mark, Roy, Stephanie, Doyle, Orla, Leavitt, Nadea, Rigg, John

Objectives To develop and evaluate machine learning models to detect suspected undiagnosed nonalcoholic steatohepatitis (NASH) patients for diagnostic screening and clinical management. Methods In this retrospective observational noninterventional st

Externí odkaz: http://arxiv.org/abs/2203.03365

Machine learning using longitudinal prescription and medical claims for the detection of non-alcoholic steatohepatitis (NASH).

Autor: Yasar O; Real World Solutions, IQVIA, London, UK., Long P; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA Patrick.long@iqvia.com., Harder B; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Marshall H; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Bhasin S; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Lee S; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Delegge M; Therapeutic Center of Excellence, IQVIA, Durham, North Carolina, USA., Roy S; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Doyle O; Real World Solutions, IQVIA, London, UK., Leavitt N; Real World Solutions, IQVIA, Plymouth Meeting, Pennsylvania, USA., Rigg J; Real World Solutions, IQVIA, London, UK.

Publikováno v: BMJ health & care informatics [BMJ Health Care Inform] 2022 Mar; Vol. 29 (1).