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DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.

, , , , , , and . J. Biomed. Informatics, (February 2023)

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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)DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing., , , , , , and . CoRR, (2022)Untapped Potential of Clinical Text for Opioid Surveillance., , , , , , , , , and 3 other author(s). AMIA, AMIA, (2019)Merkle-Tree Based Approach for Ensuring Integrity of Electronic Medical Records., , and . UEMCON, page 983-987. IEEE, (2018)DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing., , , , , , and . J. Biomed. Informatics, (February 2023)Development and application of a high throughput natural language processing architecture to convert all clinical documents in a clinical data warehouse into standardized medical vocabularies., , , , , , , , , and 1 other author(s). J. Am. Medical Informatics Assoc., 26 (11): 1364-1369 (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)Multi-Task Training with In-Domain Language Models for Diagnostic Reasoning., , , , , and . ClinicalNLP@ACL, page 78-85. Association for Computational Linguistics, (2023)The Addition of United States Census-Tract Data Does Not Improve the Prediction of Substance Misuse., , , , , , and . AMIA, AMIA, (2021)