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Computational models of disfluencies : fillers and discourse markers in spoken language understanding ; Modèles computationnels des disfluences dans le traitement de la parole
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In: https://tel.archives-ouvertes.fr/tel-03653211 ; Computer science. Institut Polytechnique de Paris, 2022. English. ⟨NNT : 2022IPPAT001⟩ (2022)
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An Empirical Comparison of Portuguese and Multilingual BERT Models for Auto-Classification of NCM Codes in International Trade
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 8 (2022)
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Hebrew Transformed: Machine Translation of Hebrew Using the Transformer Architecture
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Using Geolocated Text to Quantify Location in Real Estate Appraisal
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TSM: Measuring the Enticement of Honeyfiles with Natural Language Processing
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CorpusExplorer ; Eine Software zur korpuspragmatischen Analyse
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An Approach Utilizing Linguistic Features for Fake News Detection
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In: IFIP Advances in Information and Communication Technology ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) ; https://hal.inria.fr/hal-03287679 ; 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Jun 2021, Hersonissos, Crete, Greece. pp.646-658, ⟨10.1007/978-3-030-79150-6_51⟩ (2021)
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Playing With Unicorns: AI Dungeon and Citizen NLP
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In: Digital Humanities Quarterly, vol 14, iss 4 (2021)
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Towards a Discourse-Level Natural Language Processing Algorithm: Characterizing Tumor Existence, Change of Existence, and its Progression from Unstructured Radiology Reports
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Huang, Ruiqi. - : eScholarship, University of California, 2021
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Abstract:
Cancer has been the second leading cause of death in the US[1]. To provide care for cancer patients and retrospectively study this disease, clinicians and researchers need to manually analyze patient-level medical history to determine whether a tumor exists, has the state of existence changed, and does the change implicate disease progression. With the growing adoption of the electronic health records (EHRs), it is now possible to access these data and automate the discourse-level analysis on unstructured clinical texts using natural language processing (NLP) techniques.This thesis focuses on developing, training, and evaluating a transformer-based text classification algorithm that will capture contexts from unstructured radiology reports and output the discourse-level analysis on the tumor status and its progression through three conceptual frames: existence of a tumor, change of existence, and significance of change. This is the first clinical NLP work that conceptualize these representations using a wide range of systemic inferences, including contexts from presuppositions. The model shows promising results and can be extended to improve on casual reasoning, logical reasoning, numerical reasoning, and temporal reasoning in the future.
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Keyword:
Bioengineering; Computer science; Deep learning method; Linguistics; Natural Language Processing (NLP); Presuppositions; Tumor Existence; Tumor Progression; Unstructured Radiology Report
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URL: https://escholarship.org/uc/item/3t0067df
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The First Annotated Corpus of Historical Basque
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In: ISSN: 2055-7671 ; EISSN: 2055-768X ; Digital Scholarship in the Humanities ; https://hal.archives-ouvertes.fr/hal-03505658 ; Digital Scholarship in the Humanities, Oxford University Press, 2021, ⟨10.1093/llc/fqab066⟩ (2021)
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| 11 |
CorpusExplorer ... : Eine Software zur korpuspragmatischen Analyse ...
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The Unsolved Problem of Language Identification: A GMM-based Approach ...
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The Unsolved Problem of Language Identification: A GMM-based Approach ...
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| 14 |
The TSL machine: parser, lemma analysis, sentiment analysis and autocoding for Telegram chats ...
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The TSL machine: parser, lemma analysis, sentiment analysis and autocoding for Telegram chats ...
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The TSL machine: parser, lemma analysis, sentiment analysis and autocoding for Telegram chats ...
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Free Software Tools for Computational Linguistics: An Overview ...
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Free Software Tools for Computational Linguistics: An Overview ...
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