Cooperative Joint Attentive Network for Patient Outcome Prediction on Irregular Multi-Rate Multivariate Health Data

Qingxiong Tan, Mang Ye*, Grace Lai Hung Wong, Pong Chi Yuen

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Due to the dynamic health status of patients and discrepant stability of physiological variables, health data often presents as irregular multi-rate multivariate time series (IMR-MTS) with significantly varying sampling rates. Existing methods mainly study changes of IMR-MTS values in the time domain, without considering their different dominant frequencies and varying data quality. Hence, we propose a novel Cooperative Joint Attentive Network (CJANet) to analyze IMR-MTS in frequency domain, which adaptively handling discrepant dominant frequencies while tackling diverse data qualities caused by irregular sampling. In particular, novel dual-channel joint attention is designed to jointly identify important magnitude and phase signals while detecting their dominant frequencies, automatically enlarging the positive influence of key variables and frequencies. Furthermore, a new cooperative learning module is introduced to enhance information exchange between magnitude and phase channels, effectively integrating global signals to optimize the network. A frequency-aware fusion strategy is finally designed to aggregate the learned features. Extensive experimental results on real-world medical datasets indicate that CJANet significantly outperforms existing methods and provides highly interpretable results.

Original languageEnglish
Title of host publicationProceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
EditorsZhi-Hua Zhou
PublisherInternational Joint Conferences on Artificial Intelligence
Pages1586-1592
Number of pages7
ISBN (Electronic)9780999241196
DOIs
Publication statusPublished - Aug 2021
Event30th International Joint Conference on Artificial Intelligence, IJCAI 2021 - Virtual, Online, Canada
Duration: 19 Aug 202127 Aug 2021
https://ijcai-21.org/#
https://www.ijcai.org/proceedings/2021/

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference30th International Joint Conference on Artificial Intelligence, IJCAI 2021
Country/TerritoryCanada
CityVirtual, Online
Period19/08/2127/08/21
Internet address

Scopus Subject Areas

  • Artificial Intelligence

User-Defined Keywords

  • Data Mining
  • Mining Spatial
  • Temporal Data

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