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MUST-AI: Multisource surveillance tool - Avian influenza
Acte de colloque   Open Access

MUST-AI: Multisource surveillance tool - Avian influenza

Carlène Trevennec, Pierre Pompidor, Samira Bououda, Julien Rabatel et Mathieu Roche
28th International Conference on Knowledge Based and Intelligent information and Engineering Systems (KES 2024), (246), p.3034-3043
Procedia Computer Science
28. International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES 2024) (Sevilla, Spain, 11/09/2024–13/09/2024)
2024

Résumé

Epidemic intelligence Event-based surveillance Data fusion Highly pathogenic avian influenza One Health
The multisource surveillance tool (MUST) is a platform for collecting, gathering, and visualizing different sources of information related to health events and highly pathogenic avian influenza in mammals (HPAIM). MUST-AI constitutes the first part of the MUST tool, which centralizes health information relating to cases of HPAIM since January 1, 2021, and comes from 3 different notification sources, an official notification source confirmed by public health institutions (i.e., WAHIS) and two other alternative unofficial sources that collect events from online media (PADI-web) and expert networks (ProMED). Owing to the use of natural language processing (NLP) algorithms, HPAIM events are represented on an interactive map associated with a graph that represents their distribution over a given time interval. This paper presents new tools and approaches for data fusion and experiments for selecting data to integrate into MUST that are related to HPAIM events.

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