Добірка наукової літератури з теми "Epidemic event extraction"
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Статті в журналах з теми "Epidemic event extraction"
Lejeune, Gaël, Romain Brixtel, Antoine Doucet, and Nadine Lucas. "Multilingual event extraction for epidemic detection." Artificial Intelligence in Medicine 65, no. 2 (October 2015): 131–43. http://dx.doi.org/10.1016/j.artmed.2015.06.005.
Повний текст джерелаHan, Xuehua, Juanle Wang, Min Zhang, and 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, no. 8 (April 17, 2020): 2788. http://dx.doi.org/10.3390/ijerph17082788.
Повний текст джерелаSaba, Djamel, Abdelkader Hadidi, Omar Cheikhrouhou, Monia Hamdi, and Habib Hamam. "Development of an Ontology-Based Solution to Reduce the Spread of Viruses." Applied Sciences 12, no. 22 (November 21, 2022): 11839. http://dx.doi.org/10.3390/app122211839.
Повний текст джерелаAbdelkoui, Feriel, and Mohamed-Khireddine Kholladi. "Extracting Criminal-Related Events from Arabic Tweets." Journal of Information Technology Research 10, no. 3 (July 2017): 34–47. http://dx.doi.org/10.4018/jitr.2017070103.
Повний текст джерелаLibin, Pieter J. K., Lander Willem, Timothy Verstraeten, Andrea Torneri, Joris Vanderlocht, and Niel Hens. "Assessing the feasibility and effectiveness of household-pooled universal testing to control COVID-19 epidemics." PLOS Computational Biology 17, no. 3 (March 9, 2021): e1008688. http://dx.doi.org/10.1371/journal.pcbi.1008688.
Повний текст джерелаPisano, Carlo. "Strategies for Post-COVID Cities: An Insight to Paris En Commun and Milano 2020." Sustainability 12, no. 15 (July 22, 2020): 5883. http://dx.doi.org/10.3390/su12155883.
Повний текст джерелаAdamson, Rebecca. "Vulnerabilities of Women in Extractive Industries." ANTYAJAA: Indian Journal of Women and Social Change 2, no. 1 (June 2017): 24–31. http://dx.doi.org/10.1177/2455632717714134.
Повний текст джерелаOmoniwa, D. O., C. N. Chinyere, E. R. Agusi, N. Mkpuma2, J. S. Oyetunde, O. E. Igah, J. Adole, A. M. Adidu-Omoniwa, and C. A. Meseko. "Serological and molecular investigation of canine influenza virus in Plateau State, Nigeria." Sokoto Journal of Veterinary Sciences 20, no. 3 (October 17, 2022): 212–15. http://dx.doi.org/10.4314/sokjvs.v20i3.8.
Повний текст джерелаPark, Chulmin, Won-Bok Kim, Sung-Yeon Cho, Eun-Jee Oh, Hyeyoung Lee, Kyungjoon Kang, Yoonsuk Lee, and 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 (February 13, 2020): 1–13. http://dx.doi.org/10.1155/2020/3865707.
Повний текст джерелаGagarina, G. Yu, L. S. Arkhipova, and D. A. Sizova. "Labour Productivity as Indicator of Regional Economy Efficiency." Vestnik of the Plekhanov Russian University of Economics, no. 6 (December 22, 2021): 83–92. http://dx.doi.org/10.21686/2413-2829-2021-6-83-92.
Повний текст джерелаДисертації з теми "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.
Повний текст джерелаEpidemic 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
Книги з теми "Epidemic event extraction"
Bianconi, Ginestra. Multilayer Networks. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198753919.001.0001.
Повний текст джерелаЧастини книг з теми "Epidemic event extraction"
Mutuvi, Stephen, Emanuela Boros, Antoine Doucet, Gaël Lejeune, Adam Jatowt, and Moses Odeo. "Multilingual Epidemic Event Extraction." In Lecture Notes in Computer Science, 139–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91669-5_12.
Повний текст джерелаMutuvi, Stephen, Emanuela Boros, Antoine Doucet, Gaël Lejeune, Adam Jatowt, and Moses Odeo. "Token-Level Multilingual Epidemic Dataset for Event Extraction." In 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.
Повний текст джерелаLi, Jingwei, Wayne Huang, and Ping Chen. "LDA Based Event Extraction: Detecting Influenza Epidemics Using Microblog." In Data Science, 30–33. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24474-7_5.
Повний текст джерелаSoussan, Tariq, and Marcello Trovati. "Information Extraction From Social Media for Epidemic Models." In Advances in Data Mining and Database Management, 125–39. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-6736-4.ch007.
Повний текст джерелаPatel, Haris, Riyâz Patel, Djamel Zitouni, Benjamin Guinhouya, Mathilde Fruchart, and Antoine Lamer. "Automated Twitter Extraction and Visual Analytics with Dashboards: Development and First Experimentations." In Studies in Health Technology and Informatics. IOS Press, 2022. http://dx.doi.org/10.3233/shti220562.
Повний текст джерелаNawaz, M. Saqib, Raza Ul Mustafa, and M. Ikram Ullah Lali. "Role of Online Data from Search Engine and Social Media in Healthcare Informatics." In Advances in Bioinformatics and Biomedical Engineering, 272–93. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2607-0.ch011.
Повний текст джерелаТези доповідей конференцій з теми "Epidemic event extraction"
Sahnoun, Sihem, and Gaël Lejeune. "Multilingual Epidemic Event Extraction : From simple Classification methods to Open Information Extraction (OIE) and Ontology." In 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.
Повний текст джерелаJarvis, David, Angela Edwards, and Narayan Bhattarai. "Extraction and Production of Keratin-Based Nanofibers for Biomedical Applications." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64501.
Повний текст джерелаNajeeb, Abdul, Abhishek Sachan, Ashutosh Tomer, and Ayushi Prakash. "Face Mask Detection Using OpenCV." In International Research Conference on IOT, Cloud and Data Science. Switzerland: Trans Tech Publications Ltd, 2023. http://dx.doi.org/10.4028/p-2ffx83.
Повний текст джерелаЗвіти організацій з теми "Epidemic event extraction"
Tang, Jiqin, Gong Zhang, Jinxiao Xing, Ying Yu, and 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, January 2022. http://dx.doi.org/10.37766/inplasy2022.1.0032.
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