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A Transfer Learning Causal Approach to Evaluate Racial/Ethnic and Geographic Variation in Outcomes Following Congenital Heart Surgery
March 22, 2024, 4:47 a.m. | Larry Han, Yi Zhang, Meena Nathan, John E. Mayer, Jr., Sara K. Pasquali, Katya Zelevinsky, Rui Duan, Sharon-Lise T. Normand
stat.ML updates on arXiv.org arxiv.org
Abstract: Congenital heart defects (CHD) are the most prevalent birth defects in the United States and surgical outcomes vary considerably across the country. The outcomes of treatment for CHD differ for specific patient subgroups, with non-Hispanic Black and Hispanic populations experiencing higher rates of mortality and morbidity. A valid comparison of outcomes within racial/ethnic subgroups is difficult given large differences in case-mix and small subgroup sizes. We propose a causal inference framework for outcome assessment and …
abstract arxiv birth causal country defects patient racial stat.ap stat.me stat.ml subgroups surgery transfer transfer learning treatment type united united states variation
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