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LivingNER corpus: Named entity recognition, normalization & classification of species, pathogens and food ...
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LivingNER corpus: Named entity recognition, normalization & classification of species, pathogens and food ...
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DisTEMIST corpus: detection and normalization of disease mentions in spanish clinical cases ...
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DisTEMIST corpus: detection and normalization of disease mentions in spanish clinical cases ...
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Deep Learning with Word Embedding Improves Kazakh Named-Entity Recognition
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In: Information; Volume 13; Issue 4; Pages: 180 (2022)
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Analyzing COVID-19 Medical Papers Using Artificial Intelligence: Insights for Researchers and Medical Professionals
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In: Big Data and Cognitive Computing; Volume 6; Issue 1; Pages: 4 (2022)
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Abstract:
Since the beginning of the COVID-19 pandemic almost two years ago, there have been more than 700,000 scientific papers published on the subject. An individual researcher cannot possibly get acquainted with such a huge text corpus and, therefore, some help from artificial intelligence (AI) is highly needed. We propose the AI-based tool to help researchers navigate the medical papers collections in a meaningful way and extract some knowledge from scientific COVID-19 papers. The main idea of our approach is to get as much semi-structured information from text corpus as possible, using named entity recognition (NER) with a model called PubMedBERT and Text Analytics for Health service, then store the data into NoSQL database for further fast processing and insights generation. Additionally, the contexts in which the entities were used (neutral or negative) are determined. Application of NLP and text-based emotion detection (TBED) methods to COVID-19 text corpus allows us to gain insights on important issues of diagnosis and treatment (such as changes in medical treatment over time, joint treatment strategies using several medications, and the connection between signs and symptoms of coronavirus, etc.).
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Keyword:
BERT; COVID-19; knowledge extraction; knowledge graphs; NER; NLP; text-based emotion detection (TBED); transfer learning
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URL: https://doi.org/10.3390/bdcc6010004
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Creating Biographical Networks from Chinese and English Wikipedia
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In: https://halshs.archives-ouvertes.fr/halshs-03217972 ; 2021 (2021)
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Sentiment Analysis of Arabic Documents
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In: Natural Language Processing for Global and Local Business ; https://hal.archives-ouvertes.fr/hal-03124729 ; Fatih Pinarbasi; M. Nurdan Taskiran. Natural Language Processing for Global and Local Business, pp.307-331, 2021, 9781799842408. ⟨10.4018/978-1-7998-4240-8.ch013⟩ ; https://www.igi-global.com/ (2021)
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WEIR-P: An Information Extraction Pipeline for the Wastewater Domain
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In: RCIS 2021 - 5th International Conference on Research Challenges in Information Science ; https://hal.archives-ouvertes.fr/hal-03211461 ; RCIS 2021 - 5th International Conference on Research Challenges in Information Science, May 2021, Virtual, Cyprus (2021)
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Event Study: Advanced Machine Learning and Statistical Technique for Analyzing Sustainability in Banking Stocks
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In: Mathematics; Volume 9; Issue 24; Pages: 3319 (2021)
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Ensemble of Deep Masked Language Models for Effective Named Entity Recognition in Health and Life Science Corpora
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In: ISSN: 2504-0537 ; Frontiers in research metrics and analytics, Vol. 6 (2021) P. 689803 (2021)
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The Comparison Between the Tools for Named Entity Recognition
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French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus
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In: CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-02678358 ; CMLC-8 - 8th Workshop on the Challenges in the Management of Large Corpora, May 2020, Marseille, France ; https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/CMLC-8book.pdf (2020)
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UNER: Universal Named-Entity Recognition Framework ...
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Alves, Diego. - : Leibniz Universität Hannover (LUH),L3S Research Center,CLEOPATRA ITN, 2020
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Cantemist guidelines: neoplasms morphology annotation and mapping to CIEO-3 ...
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Cantemist guidelines: neoplasms morphology annotation and mapping to CIEO-3 ...
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Cantemist corpus: gold standard of oncology clinical cases annotated with CIE-O 3 terminology ...
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Cantemist corpus: gold standard of oncology clinical cases annotated with CIE-O 3 terminology ...
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Cantemist guidelines: neoplasms morphology annotation and mapping to CIEO-3 ...
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