Proceedings:
No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations
Volume
Issue:
Proceedings of the AAAI Conference on Artificial Intelligence, 36
Track:
AAAI Student Abstract and Poster Program
Downloads:
Abstract:
For better monitoring and controlling influenza, WHO has launched FluNet (recently integrated to FluMART) to provide a unified platform for participating countries to routinely collect influenza-related syndromic, epidemiological and virological data. However, the reported data were incomplete.We propose a novel surveillance system based on data from multiple sources to accurately assess the epidemic status of different countries, especially for those with missing surveillance data in some periods. The proposed method can automatically select a small set of reliable and informative indicators for assessing the underlying epidemic status and proper supporting data to train the predictive model. Our proactive selection method outperforms three other out-of-box methods (linear regression, multilayer perceptron, and long-short term memory) to make accurate predictions.
DOI:
10.1609/aaai.v36i11.21659
AAAI
Proceedings of the AAAI Conference on Artificial Intelligence, 36