Literatura académica sobre el tema "Epidemic event extraction"
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Artículos de revistas sobre el tema "Epidemic event extraction"
Lejeune, Gaël, Romain Brixtel, Antoine Doucet y Nadine Lucas. "Multilingual event extraction for epidemic detection". Artificial Intelligence in Medicine 65, n.º 2 (octubre de 2015): 131–43. http://dx.doi.org/10.1016/j.artmed.2015.06.005.
Texto completoHan, Xuehua, Juanle Wang, Min Zhang y Xiaojie Wang. "Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China". International Journal of Environmental Research and Public Health 17, n.º 8 (17 de abril de 2020): 2788. http://dx.doi.org/10.3390/ijerph17082788.
Texto completoSaba, Djamel, Abdelkader Hadidi, Omar Cheikhrouhou, Monia Hamdi y Habib Hamam. "Development of an Ontology-Based Solution to Reduce the Spread of Viruses". Applied Sciences 12, n.º 22 (21 de noviembre de 2022): 11839. http://dx.doi.org/10.3390/app122211839.
Texto completoAbdelkoui, Feriel y Mohamed-Khireddine Kholladi. "Extracting Criminal-Related Events from Arabic Tweets". Journal of Information Technology Research 10, n.º 3 (julio de 2017): 34–47. http://dx.doi.org/10.4018/jitr.2017070103.
Texto completoLibin, Pieter J. K., Lander Willem, Timothy Verstraeten, Andrea Torneri, Joris Vanderlocht y Niel Hens. "Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics". PLOS Computational Biology 17, n.º 3 (9 de marzo de 2021): e1008688. http://dx.doi.org/10.1371/journal.pcbi.1008688.
Texto completoPisano, Carlo. "Strategies for Post-COVID Cities: An Insight to Paris En Commun and Milano 2020". Sustainability 12, n.º 15 (22 de julio de 2020): 5883. http://dx.doi.org/10.3390/su12155883.
Texto completoAdamson, Rebecca. "Vulnerabilities of Women in Extractive Industries". ANTYAJAA: Indian Journal of Women and Social Change 2, n.º 1 (junio de 2017): 24–31. http://dx.doi.org/10.1177/2455632717714134.
Texto completoOmoniwa, D. O., C. N. Chinyere, E. R. Agusi, N. Mkpuma2, J. S. Oyetunde, O. E. Igah, J. Adole, A. M. Adidu-Omoniwa y C. A. Meseko. "Serological and molecular investigation of canine influenza virus in Plateau State, Nigeria". Sokoto Journal of Veterinary Sciences 20, n.º 3 (17 de octubre de 2022): 212–15. http://dx.doi.org/10.4314/sokjvs.v20i3.8.
Texto completoPark, Chulmin, Won-Bok Kim, Sung-Yeon Cho, Eun-Jee Oh, Hyeyoung Lee, Kyungjoon Kang, Yoonsuk Lee y Dong-Gun Lee. "A Simple Method for the Design and Development of Flavivirus NS1 Recombinant Proteins Using an In Silico Approach". BioMed Research International 2020 (13 de febrero de 2020): 1–13. http://dx.doi.org/10.1155/2020/3865707.
Texto completoGagarina, G. Yu, L. S. Arkhipova y D. A. Sizova. "Labour Productivity as Indicator of Regional Economy Efficiency". Vestnik of the Plekhanov Russian University of Economics, n.º 6 (22 de diciembre de 2021): 83–92. http://dx.doi.org/10.21686/2413-2829-2021-6-83-92.
Texto completoTesis sobre el tema "Epidemic event extraction"
Mutuvi, Stephen. "Epidemic Event Extraction in Multilingual and Low-resource Settings". Electronic Thesis or Diss., La Rochelle, 2022. http://www.theses.fr/2022LAROS044.
Texto completoEpidemic event extraction aims to extract incidents of public health importance from text, such as disease outbreaks. While event extraction has been extensively researched for high-resource languages such as English, existing systems for epidemic event extraction are sub-optimal for low-resource, multilingual settings due to training data scarcity. First, we tackle the data scarcity challenge by transforming and annotating an existing document-level multilingual dataset into a token-level annotated dataset suitable for supervised sequence learning. Second, we formulate the event extraction task as a sequence labeling task and utilize the token-level annotated dataset to train supervised machine and deep learning models for epidemic event extraction. The results show that pre-trained language models produced the best overall performance across all the evaluated languages. Third, we propose a domain adaptation technique by including epidemiological entities (disease names and locations) in the vocabulary of pre-trained models. Incorporating the entities positively impacted the tokenization quality, contributing to model performance improvement. Finally, we evaluate self-training and observe that the approach performs marginally better than models trained using supervised learning
Libros sobre el tema "Epidemic event extraction"
Bianconi, Ginestra. Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.001.0001.
Texto completoCapítulos de libros sobre el tema "Epidemic event extraction"
Mutuvi, Stephen, Emanuela Boros, Antoine Doucet, Gaël Lejeune, Adam Jatowt y Moses Odeo. "Multilingual Epidemic Event Extraction". En Lecture Notes in Computer Science, 139–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91669-5_12.
Texto completoMutuvi, Stephen, Emanuela Boros, Antoine Doucet, Gaël Lejeune, Adam Jatowt y Moses Odeo. "Token-Level Multilingual Epidemic Dataset for Event Extraction". En Linking Theory and Practice of Digital Libraries, 55–59. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86324-1_6.
Texto completoLi, Jingwei, Wayne Huang y Ping Chen. "LDA Based Event Extraction: Detecting Influenza Epidemics Using Microblog". En Data Science, 30–33. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24474-7_5.
Texto completoSoussan, Tariq y Marcello Trovati. "Information Extraction From Social Media for Epidemic Models". En Advances in Data Mining and Database Management, 125–39. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6736-4.ch007.
Texto completoPatel, Haris, Riyâz Patel, Djamel Zitouni, Benjamin Guinhouya, Mathilde Fruchart y Antoine Lamer. "Automated Twitter Extraction and Visual Analytics with Dashboards: Development and First Experimentations". En Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220562.
Texto completoNawaz, M. Saqib, Raza Ul Mustafa y M. Ikram Ullah Lali. "Role of Online Data from Search Engine and Social Media in Healthcare Informatics". En Advances in Bioinformatics and Biomedical Engineering, 272–93. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2607-0.ch011.
Texto completoActas de conferencias sobre el tema "Epidemic event extraction"
Sahnoun, Sihem y Gaël Lejeune. "Multilingual Epidemic Event Extraction : From simple Classification methods to Open Information Extraction (OIE) and Ontology". En International Conference Recent Advances in Natural Language Processing. INCOMA Ltd. Shoumen, BULGARIA, 2021. http://dx.doi.org/10.26615/978-954-452-072-4_138.
Texto completoJarvis, David, Angela Edwards y Narayan Bhattarai. "Extraction and Production of Keratin-Based Nanofibers for Biomedical Applications". En ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64501.
Texto completoNajeeb, Abdul, Abhishek Sachan, Ashutosh Tomer y Ayushi Prakash. "Face Mask Detection Using OpenCV". En International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-2ffx83.
Texto completoInformes sobre el tema "Epidemic event extraction"
Tang, Jiqin, Gong Zhang, Jinxiao Xing, Ying Yu y Tao Han. Network Meta-analysis of Heat-clearing and Detoxifying Oral Liquid of Chinese Medicines in Treatment of Children’s Hand-foot-mouth Disease:a protocol for systematic review. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, enero de 2022. http://dx.doi.org/10.37766/inplasy2022.1.0032.
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