29 November 2018

Liu, Fan, Zhou, X, Wang, Z, Wang, T and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2018) Identification of Hypertension by Mining Class Association Rules from Multi-dimensional Features. In: 2018 24th International Conference on Pattern Recognition (ICPR), 20 Aug 2018 - 24 Aug 2018, Beijing, China.

22 March 2019

Liu, Fan, Zhou, Xingshe, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Zhu, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2019) Arrhythmias classification by integrating stacked bidirectional LSTM and two-dimensional CNN. In: PAKDD 2019, 14 April 2019-17 April 2019, Macau, China.

1 April 2019

Liu, Fan, Zhou, Xingshe, Wang, Zhu, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2019) Unobtrusive Mattress-Based Identification of Hypertension by Integrating Classification and Association Rule Mining. Sensors, 19 (7). ISSN 1424-8220

16 April 2019

Liu, Fan, Zhou, Xingshe, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Zhu, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2019) A LSTM and CNN Based Assemble Neural Network Framework for Arrhythmias Classification. In: 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019), 12 May 2019 - 17 May 2019, Brighton, United Kingdom.

30 September 2019

Liu, Fan, Zhou, Xingshe, Wang, Tianben, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Zhu, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2019) An Attention-based Hybrid LSTM-CNN Model for Arrhythmias Classification. In: 2019 International Joint Conference on Neural Networks (IJCNN), 14 Jul 2019 - 19 Jul 2019, Budapest, Hungary.

6 August 2020

Liu, Fan ORCID: 0000-0003-2931-1737, Zhou, Xingshe, Cao, Jinli ORCID: 0000-0002-0221-6361, Wang, Zhu ORCID: 0000-0003-2368-8947, Wang, Tianben, Wang, Hua ORCID: 0000-0002-8465-0996 and Zhang, Yanchun ORCID: 0000-0002-5094-5980 (2020) Anomaly Detection in Quasi-Periodic Time Series based on Automatic Data Segmentation and Attentional LSTM-CNN. IEEE Transactions on Knowledge and Data Engineering. ISSN 1041-4347