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Useful blunders: Can automated speech recognition errors improve downstream dementia classification?

, , , and . J. Biomed. Informatics, (2024)

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Named Entity Recognition in Prehospital Trauma Care., , , , , , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 1586-1587. IOS Press, (2019)Comparing NLP Systems to Extract Entities of Eligibility Criteria in Dietary Supplements Clinical Trials Using NLP-ADAPT., , , , , , and . AIME, volume 12299 of Lecture Notes in Computer Science, page 67-77. Springer, (2020)Conversational Agent for Daily Living Assessment Coaching Demo., , , , and . EACL (System Demonstrations), page 321-328. Association for Computational Linguistics, (2021)Creating a Test Corpus of Clinical Notes Manually Tagged for Part-of-Speech Information., , and . NLPBA/BioNLP, (2004)Useful blunders: Can automated speech recognition errors improve downstream dementia classification?, , , and . J. Biomed. Informatics, (2024)Electronic Progress Note Reading Patterns: An Eye Tracking Analysis., , , , , and . MedInfo, volume 264 of Studies in Health Technology and Informatics, page 1684-1685. IOS Press, (2019)Abbreviation and Acronym Disambiguation in Clinical Discourse., , and . AMIA, AMIA, (2005)Crossing the "Cookie Theft" Corpus Chasm: Applying What BERT Learns From Outside Data to the ADReSS Challenge Dementia Detection Task., , , , and . Frontiers Comput. Sci., (2021)Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies., , , and . ACL (Findings), page 6363-6377. Association for Computational Linguistics, (2024)GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Models., , , , and . ACL (1), page 1866-1877. Association for Computational Linguistics, (2022)