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Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups., , , , , , , , and . J. Am. Medical Informatics Assoc., 28 (11): 2393-2403 (2021)A multi-label classifier to screen different types of substance misuse in hospitalized patients., , , , , and . AMIA, AMIA, (2021)Transatlantic transferability and replicability of machine-learning algorithms to predict mental health crises., , , , , and . npj Digit. Medicine, (2024)Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation., , , , , , , , , and . J. Am. Medical Informatics Assoc., 26 (3): 254-261 (2019)Untapped Potential of Clinical Text for Opioid Surveillance., , , , , , , , , and 3 other author(s). AMIA, AMIA, (2019)Publicly available machine learning models for identifying opioid misuse from the clinical notes of hospitalized patients., , , , , , and . BMC Medical Informatics Decis. Mak., 20 (1): 79 (2020)Identification of Latent Subtypes of Patients with Opioid Misuse., , , , , , and . AMIA, AMIA, (2019)