Researchers implemented a computerized clinical decision support (cCDS) tool in three primary care clinics for a three-month period to screen for Metabolic-Associated Steatotic Liver Disease (MASLD) at risk for advanced fibrosis. ^[1] The intervention took place within primary care settings, utilizing the cCDS system to identify patients with MASLD who may be progressing toward advanced liver scarring. ^[1] Jani Liimatta concluded that machine learning should be viewed as a tool to augment and support clinical expertise rather than something to replace it. ^[2] The read here is that the deployment of the cCDS tool aligns with the view that machine learning serves to support rather than replace clinical judgment. ^[2]