Evidence map›Paper›PMID 34566574›Full record

ArticleFrontiers in neuroscience2021

Identification of Epileptic EEG Signals Through TSK Transfer Learning Fuzzy System.

Zhaoliang Zheng, Xuan Dong, Jian Yao, Leyuan Zhou, Yang Ding, Aiguo Chen

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Zhaoliang ZhengSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China.
Xuan DongDepartment of Tuberculosis and Respiratory Diseases, Wuhan Jinyintan Hospital, Wuhan, China.
Jian YaoSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China.
Leyuan ZhouDepartment of Radiotherapy, Affiliated Hospital, Jiangnan University, Wuxi, China.
Yang DingDepartment of Radiotherapy, Affiliated Hospital, Jiangnan University, Wuxi, China.
Aiguo ChenSchool of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a new model to identify epilepsy EEG signals. Some existing intelligent recognition technologies require that the training set and test set have the same distribution when recognizing EEG signals, some only consider reducing the marginal distribution distance of the data while ignoring the intra-class information of data, and some lack of interpretability. To address these deficiencies, we construct a TSK transfer learning fuzzy system (TSK-TL) based on the easy-to-interpret TSK fuzzy system the transfer learning method. The proposed model is interpretable. By using the information contained in the source domain and target domains more effectively, the requirements for data distribution are further relaxed. It realizes the identification of epilepsy EEG signals in data drift scene. The experimental results show that compared with the existing algorithms, TSK-TL has better performance in EEG recognition of epilepsy.

Indexed as

epilepsy EEG signalsinterpretabilityknowledge learningtransfer learningTSK fuzzy system

Identifiers

PMID34566574
PMCPMC8462357

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.