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MindLab-UNAL: Comparing Metamap and T-mapper for Medical Concept Extraction in SemEval 2014 Task 7

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Machine Learning for the Developing World., , , and . ACM Trans. Manag. Inf. Syst., 9 (2): 9:1-9:14 (2018)Diversity in sociotechnical machine learning systems., and . Big Data Soc., 9 (1): 205395172210820 (January 2022)Toward Supporting Perceptual Complementarity in Human-AI Collaboration via Reflection on Unobservables., , , and . Proc. ACM Hum. Comput. Interact., 7 (CSCW1): 1-20 (April 2023)MindLab-UNAL: Comparing Metamap and T-mapper for Medical Concept Extraction in SemEval 2014 Task 7., , , , and . SemEval@COLING, page 424-427. The Association for Computer Linguistics, (2014)Leveraging Expert Consistency to Improve Algorithmic Decision Support., , and . CoRR, (2021)When More Data Lead Us Astray: Active Data Acquisition in the Presence of Label Bias., , and . HCOMP, page 133-146. AAAI Press, (2022)What's in a Name? Reducing Bias in Bios without Access to Protected Attributes., , , , , , , , , and . NAACL-HLT (1), page 4187-4195. Association for Computational Linguistics, (2019)Diversity in Sociotechnical Machine Learning Systems., and . CoRR, (2021)Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms., , and . FAccT, page 1504-1515. ACM, (2022)Bias in Bios: A Case Study of Semantic Representation Bias in a High-Stakes Setting., , , , , , , , and . FAT, page 120-128. ACM, (2019)