| Autor: |
Trevennec, Carlène, Pompidor, Pierre, Bououda, Samira, Rabatel, Julien, Roche, Mathieu |
| Předmět: |
|
| Zdroj: |
Procedia Computer Science; 2024, Vol. 246, p3034-3043, 10p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
|
