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Found 5 papers, 3 papers with code
TCube: Domain-Agnostic Neural Time-series Narration
We present TCube (Time-series-to-text), a domain-agnostic neural framework for time-series narration, that couples the representation of essential time-series elements in the form of a dense knowledge graph and the translation of said knowledge graph into rich and fluent narratives through the transfer-learning capabilities of PLMs (Pre-trained Language Models).
Guided Deep List: Automating the Generation of Epidemiological Line Lists from Open Sources
Specifically, we focus on deriving epidemiological characteristics of an emerging disease and the affected population from reports of illness.
Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks
In this study, we quantify the extent to which media interest during infectious disease outbreaks is indicative of trends of reported incidence.
Characterizing Diseases from Unstructured Text: A Vocabulary Driven Word2vec Approach
Traditional disease surveillance can be augmented with a wide variety of real-time sources such as, news and social media.
Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance
Accurate real-time monitoring systems of influenza outbreaks help public health officials make informed decisions that may help save lives.
