https://www.socictopen.socict.org/files/original/dcc36c03f950a6a5e2e8e64961955f32.pdf 3a4b80091a43d74df588f034c8c9f639 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Accelerating Epidemiological Investigation Analysis by Using NLP and Knowledge Reasoning: A Case Study on COVID-19. Creator An entity primarily responsible for making the resource Jian Wang, Ke Wang, Jing Li, Jianmin Jiang, Yanfei Wang, Jing Mei, Shaochun Li Description An account of the resource COVID-19 is threatening the health of the entire human population. In order to control the spread of the disease, epidemiological investigations should be conducted, to trace the infection source of each confirmed patient and isolate their close contacts. However, the analysis on a mass of case reports in epidemiological investigation is extremely time-consuming and labor-intensive. This paper presents an end-to-end framework for automatic epidemiological case report analysis and inference, in which a Tuple-based Multi-Task Neural Network (TMT-NN) is designed and implemented for jointly recognizing epidemiological entities and relations from case reports, and an epidemiological knowledge graph and its corresponding inference engine are built to uncover the infection modes, sources and pathways. Preliminary experiments demonstrate the promising results, and we published a real data set of COVID-19 epidemiological investigation corpora at Github, as well as contributing our COVID-19 epidemiological knowledge graph to the open community OpenKG.cn. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Source A related resource from which the described resource is derived AMIA ... Annual Symposium proceedings. AMIA Symposium