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Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative., , , , , , , , , and 76 other author(s). J. Am. Medical Informatics Assoc., 29 (4): 609-618 (2022)Clinical encounter heterogeneity and methods for resolving in networked EHR data: a study from N3C and RECOVER programs., , , , , , , , , and 3 other author(s). J. Am. Medical Informatics Assoc., 30 (6): 1125-1136 (2023)De-black-boxing health AI: demonstrating reproducible machine learning computable phenotypes using the N3C-RECOVER Long COVID model in the All of Us data repository., , , , , , , , , and 4 other author(s). J. Am. Medical Informatics Assoc., 30 (7): 1305-1312 (June 2023)Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C)., , , , , , , , , and 65 other author(s). J. Am. Medical Informatics Assoc., 29 (8): 1350-1365 (2022)The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment., , , , , , , , , and 46 other author(s). J. Am. Medical Informatics Assoc., 28 (3): 427-443 (2021)Harmonizing units and values of quantitative data elements in a very large nationally pooled electronic health record (EHR) dataset., , , , , , , , , and 13 other author(s). J. Am. Medical Informatics Assoc., 29 (7): 1172-1182 (2022)