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Podcast: Surfing the MASH Tsunami
Episode: S2-E20 - 14-variable Machine Learning model identifies Probable NASH patients from Electronic Health Records
Description: Jörn Schattenberg discusses NASHmap, the first Machine Learning model that can identify patients likely to have NASH in clinical settings. Louise, Roger and guest Dr. Kris Kowdley join Jörn to discuss the model from academic, patient treatment and statistical perspectives.Prof. Schattenberg and colleagues built the NASHmap model from a NIDDK database and validated it using the Optum de-identified EHR dataset. The model includes 14 variables, some obvious, others less so, that produce an AUC of 0.82 in the NIDDK database and 0.79 in the Optum database. The episode focuses on how the model was built an...