Efficient identification of Alzheimer’s brain dynamics with Spatial-Temporal Autoencoder: A deep learning approach for diagnosing brain disorders
•An automatic EEG-based diagnosis scheme for Alzheimer’s disease (AD) with deep learning methods was proposed.•A Spatial-Temporal Autoencoder (STAE) framework was designed to estimate latent factors of EEG via unsupervised learning.•Alzheimer’s brain dynamics were inferred with STAE and manifolds in...
Saved in:
| Published in: | Biomedical signal processing and control Vol. 86; p. 104917 |
|---|---|
| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.09.2023
|
| Subjects: | |
| ISSN: | 1746-8094, 1746-8108 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | •An automatic EEG-based diagnosis scheme for Alzheimer’s disease (AD) with deep learning methods was proposed.•A Spatial-Temporal Autoencoder (STAE) framework was designed to estimate latent factors of EEG via unsupervised learning.•Alzheimer’s brain dynamics were inferred with STAE and manifolds in low-dimensional state space were used to identify AD.•STAE exhibited superior performance with high accuracy of AD identification and robust against instability in EEG recording.
Alzheimer’s disease (AD) is a progressive neurological disorder seriously affecting cognitive and behavior abilities of the older people. Accurate and early diagnosis of AD is critical for improving the therapeutic effect and alleviate the clinical symptom. In this work, we proposed an automatic EEG-based diagnosis scheme for AD patients with deep learning methods. A Spatial-Temporal Autoencoder (STAE) framework with Convolutional Neural Network (CNN)- Long Short-Term-Memory (LSTM) generative model was designed to estimate latent factors of the observed oscillatory activity in the brain from multi-channels electroencephalogram (EEG) signals via unsupervised learning. Based on latent factor analysis, Alzheimer’s brain dynamics on single-trials were inferred and temporal evolution of latent brain state was analyzed in low-dimensional state space. The study mainly showed that: i) the brain state trajectories of AD patients were distinct from healthy subjects, resulting in different forms of ring manifolds and allowing to accurately identify AD; ii) experimental results demonstrated the efficiency and flexibility of the proposed deep learning-based diagnosis scheme, by which the classification of AD patients and the normal based on clinical EEG dataset achieved an accuracy of 96.30%, a sensitivity of 97.73% and a specificity of 94.69% with a multiple layer perception (MLP) classifier; iii) compared with other approaches for latent brain dynamics estimation, STAE exhibited superior performance with high accuracy of AD identification and strongly robust against instabilities in EEG recordings. The present results reveal the neuropathological mechanism of Alzheimer’s disease with brain dynamics variations and provide a feasible diagnosis tool for brain disorders. |
|---|---|
| AbstractList | •An automatic EEG-based diagnosis scheme for Alzheimer’s disease (AD) with deep learning methods was proposed.•A Spatial-Temporal Autoencoder (STAE) framework was designed to estimate latent factors of EEG via unsupervised learning.•Alzheimer’s brain dynamics were inferred with STAE and manifolds in low-dimensional state space were used to identify AD.•STAE exhibited superior performance with high accuracy of AD identification and robust against instability in EEG recording.
Alzheimer’s disease (AD) is a progressive neurological disorder seriously affecting cognitive and behavior abilities of the older people. Accurate and early diagnosis of AD is critical for improving the therapeutic effect and alleviate the clinical symptom. In this work, we proposed an automatic EEG-based diagnosis scheme for AD patients with deep learning methods. A Spatial-Temporal Autoencoder (STAE) framework with Convolutional Neural Network (CNN)- Long Short-Term-Memory (LSTM) generative model was designed to estimate latent factors of the observed oscillatory activity in the brain from multi-channels electroencephalogram (EEG) signals via unsupervised learning. Based on latent factor analysis, Alzheimer’s brain dynamics on single-trials were inferred and temporal evolution of latent brain state was analyzed in low-dimensional state space. The study mainly showed that: i) the brain state trajectories of AD patients were distinct from healthy subjects, resulting in different forms of ring manifolds and allowing to accurately identify AD; ii) experimental results demonstrated the efficiency and flexibility of the proposed deep learning-based diagnosis scheme, by which the classification of AD patients and the normal based on clinical EEG dataset achieved an accuracy of 96.30%, a sensitivity of 97.73% and a specificity of 94.69% with a multiple layer perception (MLP) classifier; iii) compared with other approaches for latent brain dynamics estimation, STAE exhibited superior performance with high accuracy of AD identification and strongly robust against instabilities in EEG recordings. The present results reveal the neuropathological mechanism of Alzheimer’s disease with brain dynamics variations and provide a feasible diagnosis tool for brain disorders. |
| ArticleNumber | 104917 |
| Author | Zhao, Quanfa Liu, Jing Wu, Lingyun Yu, Haitao |
| Author_xml | – sequence: 1 givenname: Lingyun surname: Wu fullname: Wu, Lingyun organization: Department of Neurology, Tangshan Gongren Hospital, Tangshan 063000, China – sequence: 2 givenname: Quanfa surname: Zhao fullname: Zhao, Quanfa organization: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China – sequence: 3 givenname: Jing surname: Liu fullname: Liu, Jing organization: Department of Neurology, Tangshan Gongren Hospital, Tangshan 063000, China – sequence: 4 givenname: Haitao surname: Yu fullname: Yu, Haitao email: htyu@tju.edu.cn organization: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China |
| BookMark | eNp9kE1u2zAQRokiBZq4vUBXvIBcUpT1U2RjGG4TIEAWTdfEiBzaY8ikQCoNnFXukFWvl5NEitNNF94MhwO-D5x3wc588MjYVynmUsjy227ept7Mc5GrcVA0svrAzmVVlFktRX32rxdN8YldpLQToqgrWZyz57VzZAj9wMmOlcYbDBQ8D44vu8ct0h7jy9PfxNsI5Lk9eNiTSfyBhi3_1Y-PocvucN-HCB1f3g8BvQkW43e-5Bax5x1C9OQ3HPo-BjBb7kLklmDjQ5rm78mUQhy59Jl9dNAl_PJ-ztjvH-u71VV2c_vzerW8yYwSYsiUsVZCAbVR4EqZN41SRgLWrhI1VE1eViqXtlqAkHVZuLZdKNc2VolWlK4VasbqY66JIaWIThsa3pYfxg91Wgo9ydU7PcnVk1x9lDui-X9oH2kP8XAaujxCOC71hzDqNJk3aCmiGbQNdAp_BXYJmfE |
| CitedBy_id | crossref_primary_10_1177_09287329241291334 crossref_primary_10_3390_diagnostics15111441 crossref_primary_10_1016_j_bspc_2025_108057 crossref_primary_10_1002_ajmg_b_32979 crossref_primary_10_1016_j_bspc_2023_105703 crossref_primary_10_1016_j_cmpb_2024_108506 crossref_primary_10_1016_j_bspc_2024_106668 crossref_primary_10_1016_j_bspc_2023_105298 |
| Cites_doi | 10.1016/j.bspc.2021.103417 10.1038/s41467-022-34129-4 10.1017/S1041610213000781 10.1109/TIT.1967.1053964 10.1038/nn.3776 10.1002/ana.25380 10.1073/pnas.2212954119 10.1038/s41592-018-0109-9 10.1016/j.neuron.2017.05.025 10.1016/j.cell.2019.12.018 10.1109/TNSRE.2021.3101240 10.3233/JAD-170841 10.1016/j.neubiorev.2017.01.002 10.1073/pnas.1408900111 10.1177/155005941104200304 10.1523/JNEUROSCI.1669-18.2018 10.1159/000441447 10.1038/ncomms8759 10.1016/j.arr.2021.101482 10.1016/S1474-4422(20)30440-3 10.1038/nature11129 10.1016/j.neuron.2018.05.020 10.1177/1550059413486272 10.1073/pnas.1915984117 10.1007/BF00308809 10.1016/S0020-7373(87)80053-6 10.1109/TFUZZ.2019.2903753 10.1093/brain/awaa058 10.3389/fnins.2020.00641 10.1371/journal.pcbi.1008128 10.3233/ICA-130439 10.1109/ACCESS.2019.2912273 10.1038/s41467-017-01150-x 10.1007/s11571-014-9325-x 10.3389/fnsys.2020.00043 10.1016/j.physa.2018.05.009 10.1080/03610730590948186 10.1016/j.neuroimage.2021.118774 10.1162/neco.1997.9.8.1735 10.1016/j.neurobiolaging.2017.12.023 10.2174/156720510792231720 10.1016/j.neurobiolaging.2011.06.007 10.1592/phco.27.3.399 10.1016/j.neurobiolaging.2014.12.013 10.2967/jnumed.116.179903 10.1007/s10548-018-0674-3 10.1023/A:1022627411411 |
| ContentType | Journal Article |
| Copyright | 2023 Elsevier Ltd |
| Copyright_xml | – notice: 2023 Elsevier Ltd |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.bspc.2023.104917 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering |
| EISSN | 1746-8108 |
| ExternalDocumentID | 10_1016_j_bspc_2023_104917 S1746809423003506 |
| GroupedDBID | --- --K --M .~1 0R~ 1B1 1~. 1~5 23N 4.4 457 4G. 5GY 5VS 6J9 7-5 71M 8P~ AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALRI AAOAW AAQFI AAXUO AAYFN ABBOA ABFNM ABFRF ABJNI ABMAC ABXDB ACDAQ ACGFO ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADMUD ADTZH AEBSH AECPX AEFWE AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD AXJTR BJAXD BKOJK BLXMC CS3 DU5 EBS EFJIC EJD EO8 EO9 EP2 EP3 F5P FDB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HZ~ IHE J1W JJJVA KOM M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 RIG ROL RPZ SDF SDG SES SPC SPCBC SST SSV SSZ T5K UNMZH ~G- 9DU AATTM AAXKI AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFJKZ AFPUW AIGII AIIUN AKBMS AKYEP ANKPU APXCP CITATION EFKBS EFLBG ~HD |
| ID | FETCH-LOGICAL-c300t-3cdd1a4a8c3af6129933c1ae8f708a79267321d75a01864fbb53fb9d30b06fb03 |
| ISICitedReferencesCount | 8 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000986554400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1746-8094 |
| IngestDate | Sat Nov 29 07:02:04 EST 2025 Tue Nov 18 22:20:48 EST 2025 Tue Jul 16 04:30:46 EDT 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Deep learning Latent brain dynamics Diagnosis Alzheimer’s disease Spatial-Temporal Autoencoder |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c300t-3cdd1a4a8c3af6129933c1ae8f708a79267321d75a01864fbb53fb9d30b06fb03 |
| ParticipantIDs | crossref_citationtrail_10_1016_j_bspc_2023_104917 crossref_primary_10_1016_j_bspc_2023_104917 elsevier_sciencedirect_doi_10_1016_j_bspc_2023_104917 |
| PublicationCentury | 2000 |
| PublicationDate | September 2023 2023-09-00 |
| PublicationDateYYYYMMDD | 2023-09-01 |
| PublicationDate_xml | – month: 09 year: 2023 text: September 2023 |
| PublicationDecade | 2020 |
| PublicationTitle | Biomedical signal processing and control |
| PublicationYear | 2023 |
| Publisher | Elsevier Ltd |
| Publisher_xml | – name: Elsevier Ltd |
| References | Yu (b0135) 2020; 28 Kanda (b0210) 2014; 45 Cherry, Simmons (b0025) 2005; 31 Cover, Hart (b0265) 1967; 13 Li (b0140) 2021; 29 Therriault (b0220) 2020; 96 Tetreault (b0080) 2020; 143 Pandarinath (b0185) 2018; 15 Pandarinath (b0145) 2018; 38 Pichet (b0040) 2022; 13 Graff-Radford (b0225) 2021; 20 Shoeibi (b0125) 2022; 73 Braak, Braak (b0005) 1991; 82 Churchland (b0160) 2012; 487 Boyle (b0010) 2019; 85 J.C. Watts, et al., Serial Propagation of Distinct Strains of Aβ Prions from Alzheimer's Disease Patients. Proceedings of the National Academy of Sciences, 2014. 111 28 10323-10328. Kao (b0175) 2015; 6 Zhao (b0120) 2022; 246 Beier (b0020) 2007; 27 Whitwell (b0055) 2015; 36 Quinlan (b0270) 1987; 27 Liu (b0190) 2020; 14 Babiloni (b0085) 2018; 65 Pini (b0095) 2021; 72 Bhat (b0075) 2015; 74 Whitwell (b0230) 2017; 58 Yu (b0110) 2020; 14 Barnes (b0015) 2018; 64 Gallego (b0150) 2017; 94 Cera (b0215) 2013; 25 Franciotti (b0090) 2019; 32 Q (b0195) 2019; 7 Hochreiter, Schmidhuber (b0200) 1997; 9 Palmqvist (b0035) 2017; 8 Cueva (b0170) 2020; 117 Cunningham, Yu (b0180) 2014; 17 Vieira (b0115) 2017; 74 Wang (b0245) 2015; 9 Dauwels, Vialatte, Cichocki (b0250) 2010; 7 Yu (b0100) 2018; 506 Lin (b0155) 2020; 180 Zhang (b0255) 2013; 20 Cassani (b0045) 2018 Cai (b0105) 2020 Haan (b0060) 2008; 4 Cortes, Vapnik (b0260) 1995; 20 Cao (b0240) 2015; 25 Trambaiolli (b0130) 2011; 42 Pollock, Jazayeri (b0205) 2020; 16 C. Condello, et al., Aβ and Tau Prions Feature in the Neuropathogenesis of Down Syndrome. Proceedings of the National Academy of Sciences, 2022. 119 46 e2212954119. Agosta (b0050) 2012; 33 Remington (b0165) 2018; 98 Ouchani (b0065) 2021 Wang (b0070) 2015; 25 Yu (10.1016/j.bspc.2023.104917_b0100) 2018; 506 Whitwell (10.1016/j.bspc.2023.104917_b0055) 2015; 36 Q (10.1016/j.bspc.2023.104917_b0195) 2019; 7 Remington (10.1016/j.bspc.2023.104917_b0165) 2018; 98 Whitwell (10.1016/j.bspc.2023.104917_b0230) 2017; 58 Palmqvist (10.1016/j.bspc.2023.104917_b0035) 2017; 8 Hochreiter (10.1016/j.bspc.2023.104917_b0200) 1997; 9 Bhat (10.1016/j.bspc.2023.104917_b0075) 2015; 74 Haan (10.1016/j.bspc.2023.104917_b0060) 2008; 4 Therriault (10.1016/j.bspc.2023.104917_b0220) 2020; 96 Shoeibi (10.1016/j.bspc.2023.104917_b0125) 2022; 73 Boyle (10.1016/j.bspc.2023.104917_b0010) 2019; 85 Cunningham (10.1016/j.bspc.2023.104917_b0180) 2014; 17 Cai (10.1016/j.bspc.2023.104917_b0105) 2020 Cao (10.1016/j.bspc.2023.104917_b0240) 2015; 25 Churchland (10.1016/j.bspc.2023.104917_b0160) 2012; 487 Ouchani (10.1016/j.bspc.2023.104917_b0065) 2021 Quinlan (10.1016/j.bspc.2023.104917_b0270) 1987; 27 Pollock (10.1016/j.bspc.2023.104917_b0205) 2020; 16 Babiloni (10.1016/j.bspc.2023.104917_b0085) 2018; 65 Gallego (10.1016/j.bspc.2023.104917_b0150) 2017; 94 Zhang (10.1016/j.bspc.2023.104917_b0255) 2013; 20 Li (10.1016/j.bspc.2023.104917_b0140) 2021; 29 Kao (10.1016/j.bspc.2023.104917_b0175) 2015; 6 10.1016/j.bspc.2023.104917_b0030 Cortes (10.1016/j.bspc.2023.104917_b0260) 1995; 20 Vieira (10.1016/j.bspc.2023.104917_b0115) 2017; 74 Dauwels (10.1016/j.bspc.2023.104917_b0250) 2010; 7 Cover (10.1016/j.bspc.2023.104917_b0265) 1967; 13 Trambaiolli (10.1016/j.bspc.2023.104917_b0130) 2011; 42 Lin (10.1016/j.bspc.2023.104917_b0155) 2020; 180 Kanda (10.1016/j.bspc.2023.104917_b0210) 2014; 45 Agosta (10.1016/j.bspc.2023.104917_b0050) 2012; 33 Pichet (10.1016/j.bspc.2023.104917_b0040) 2022; 13 Franciotti (10.1016/j.bspc.2023.104917_b0090) 2019; 32 10.1016/j.bspc.2023.104917_b0235 Pandarinath (10.1016/j.bspc.2023.104917_b0185) 2018; 15 Beier (10.1016/j.bspc.2023.104917_b0020) 2007; 27 Cera (10.1016/j.bspc.2023.104917_b0215) 2013; 25 Cassani (10.1016/j.bspc.2023.104917_b0045) 2018 Barnes (10.1016/j.bspc.2023.104917_b0015) 2018; 64 Braak (10.1016/j.bspc.2023.104917_b0005) 1991; 82 Wang (10.1016/j.bspc.2023.104917_b0245) 2015; 9 Zhao (10.1016/j.bspc.2023.104917_b0120) 2022; 246 Pini (10.1016/j.bspc.2023.104917_b0095) 2021; 72 Liu (10.1016/j.bspc.2023.104917_b0190) 2020; 14 Pandarinath (10.1016/j.bspc.2023.104917_b0145) 2018; 38 Cherry (10.1016/j.bspc.2023.104917_b0025) 2005; 31 Wang (10.1016/j.bspc.2023.104917_b0070) 2015; 25 Yu (10.1016/j.bspc.2023.104917_b0110) 2020; 14 Cueva (10.1016/j.bspc.2023.104917_b0170) 2020; 117 Tetreault (10.1016/j.bspc.2023.104917_b0080) 2020; 143 Yu (10.1016/j.bspc.2023.104917_b0135) 2020; 28 Graff-Radford (10.1016/j.bspc.2023.104917_b0225) 2021; 20 |
| References_xml | – volume: 20 start-page: 273 year: 1995 end-page: 297 ident: b0260 article-title: Support-vector networks publication-title: Mach. Learn. – volume: 16 start-page: e1008128 year: 2020 ident: b0205 article-title: Engineering recurrent neural networks from task-relevant manifolds and dynamics publication-title: PLoS Comput. Biol. – volume: 45 start-page: 104 year: 2014 end-page: 112 ident: b0210 article-title: Clinician’s road map to wavelet EEG as an Alzheimer’s Disease Biomarker publication-title: Clin. EEG Neurosci. – volume: 20 start-page: 222 year: 2021 end-page: 234 ident: b0225 article-title: New insights into atypical Alzheimer's disease in the era of biomarkers publication-title: The Lancet Neurol. – volume: 8 start-page: 1214 year: 2017 ident: b0035 article-title: Earliest accumulation of Β-Amyloid occurs within the default-mode network and concurrently affects brain connectivity publication-title: Nat. Commun. – volume: 143 start-page: 1249 year: 2020 end-page: 1260 ident: b0080 article-title: Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s Disease publication-title: Brain – volume: 82 start-page: 239 year: 1991 end-page: 259 ident: b0005 article-title: Neuropathological Stageing of Alzheimer-Related Changes publication-title: Acta. Neuropathol. – start-page: 51. 14 year: 2020: ident: b0105 article-title: Functional integration and segregation in multiplex brain networks for Alzheimer's disease publication-title: Front. Neurosci. – volume: 13 start-page: 6635 year: 2022 ident: b0040 article-title: Amyloid-associated increases in soluble Tau relate to tau aggregation rates and cognitive decline in Early Alzheimer’s disease publication-title: Nat. Commun. – volume: 38 start-page: 9390 year: 2018 end-page: 9401 ident: b0145 article-title: Latent factors and dynamics in motor cortex and their application to brain-machine interfaces publication-title: J. Neurosci. – volume: 27 start-page: 221 year: 1987 end-page: 234 ident: b0270 article-title: Simplifying decision trees publication-title: Int. J. Man Mach. Stud. – volume: 7 start-page: 487 year: 2010 ident: b0250 article-title: Diagnosis of Alzheimer's Disease from EEG Signals: where are we standing? publication-title: Curr. Alzheimer Res. – volume: 25 year: 2015 ident: b0240 article-title: Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy. chaos: an interdisciplinary publication-title: J. Nonlinear Sci. – volume: 6 start-page: 7759 year: 2015 ident: b0175 article-title: Single-trial dynamics of motor cortex and their applications to brain-machine interfaces publication-title: Nat. Commun. – volume: 9 start-page: 291 year: 2015 end-page: 304 ident: b0245 article-title: Power spectral density and coherence analysis of alzheimer's EEG publication-title: Cogn. Neurodyn. – volume: 17 start-page: 1500 year: 2014 end-page: 1509 ident: b0180 article-title: Dimensionality reduction for large-scale neural recordings publication-title: Nat. Neurosci. – start-page: 1 year: 2021 end-page: 15 ident: b0065 article-title: A review of methods of diagnosis and complexity analysis of Alzheimer's disease using EEG signals publication-title: Biomed Res. Int. – volume: 42 start-page: 160 year: 2011 end-page: 165 ident: b0130 article-title: Improving Alzheimer's disease diagnosis with machine learning techniques publication-title: Clin. EEG Neurosci. – volume: 13 start-page: 21 year: 1967 end-page: 27 ident: b0265 article-title: Nearest neighbor pattern classification publication-title: IEEE Trans. Inf. Theory – volume: 14 start-page: 641 year: 2020 ident: b0110 article-title: Identification of Alzheimer's EEG with a WVG Network-Based Fuzzy Learning Approach publication-title: Front. Neurosci. – volume: 487 start-page: 51 year: 2012 end-page: 56 ident: b0160 article-title: Neural population dynamics during reaching publication-title: Nature – volume: 25 year: 2015 ident: b0070 article-title: Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum. chaos: an interdisciplinary publication-title: J. Nonlinear Sci. – volume: 20 start-page: 391 year: 2013 end-page: 405 ident: b0255 article-title: EEG-based expert system using complexity measures and probability density function control in alpha sub-band publication-title: Integr. Comput.-Aided Eng. – volume: 246 year: 2022 ident: b0120 article-title: A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in Adhd publication-title: Neuroimage – volume: 29 start-page: 1557 year: 2021 end-page: 1567 ident: b0140 article-title: Feature extraction and identification of alzheimer's disease based on latent factor of multi-channel EEG publication-title: IEEE Trans. Neural Syst. Rehabil. Eng. – start-page: 5174815 year: 2018 ident: b0045 article-title: Systematic review on resting-state EEG for Alzheimer's disease diagnosis and progression assessment publication-title: Dis. Markers – volume: 72 year: 2021 ident: b0095 article-title: Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease publication-title: Ageing Res. Rev. – volume: 28 start-page: 60 year: 2020 end-page: 71 ident: b0135 article-title: Supervised Network-Based Fuzzy Learning of EEG Signals for Alzheimer's Disease Identification publication-title: IEEE Trans. Fuzzy Syst. – volume: 73 year: 2022 ident: b0125 article-title: Detection of Epileptic Seizures on EEG signals using anfis classifier, autoencoders and fuzzy entropies publication-title: Biomed. Signal Process. Control – volume: 180 start-page: 536 year: 2020 end-page: 551.e17 ident: b0155 article-title: Cerebellar neurodynamics predict decision timing and outcome on the single-trial level publication-title: Cell – volume: 74 start-page: 58 year: 2017 end-page: 75 ident: b0115 article-title: Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: methods and applications publication-title: Neurosci. Biobehav. Rev. – volume: 98 start-page: 1005 year: 2018 end-page: 1019.e5 ident: b0165 article-title: Flexible sensorimotor computations through rapid reconfiguration of cortical dynamics publication-title: Neuron – volume: 4 start-page: T332 year: 2008 end-page: T333 ident: b0060 article-title: P1–388: resting-state oscillatory brain dynamics in Alzheimer's disease publication-title: Alzheimers Dement. – volume: 36 start-page: 1245 year: 2015 end-page: 1252 ident: b0055 article-title: Working Memory and Language Network Dysfunctions in Logopenic Aphasia: a Task-Free fMRI Comparison with Alzheimer's Dementia publication-title: Neurobiol. Aging – volume: 96 start-page: e81 year: 2020 end-page: e92 ident: b0220 article-title: Topographic Distribution of Amyloid-Β, Tau, and Atrophy in Patients with Behavioral/Dysexecutive Alzheimer Disease publication-title: Neurology – volume: 7 start-page: 53731 year: 2019 end-page: 53742 ident: b0195 article-title: Spectrum Analysis of EEG Signals Using CNN to model patient's consciousness level based on anesthesiologists' experience publication-title: IEEE Access – volume: 9 start-page: 1735 year: 1997 end-page: 1780 ident: b0200 article-title: Long short-term memory publication-title: Neural Comput. – volume: 27 start-page: 399 year: 2007 end-page: 411 ident: b0020 article-title: Treatment strategies for the behavioral symptoms of Alzheimer's disease: focus on early pharmacologic intervention publication-title: Pharmacotherapy – volume: 85 start-page: 114 year: 2019 end-page: 124 ident: b0010 article-title: Attributable risk of Alzheimer's dementia attributed to age-related neuropathologies publication-title: Ann. Neurol. – volume: 33 start-page: 1564 year: 2012 end-page: 1578 ident: b0050 article-title: Resting State fMRI in Alzheimer's Disease: beyond the default mode network publication-title: Neurobiol. Aging – reference: C. Condello, et al., Aβ and Tau Prions Feature in the Neuropathogenesis of Down Syndrome. Proceedings of the National Academy of Sciences, 2022. 119 46 e2212954119. – volume: 117 start-page: 23021 year: 2020 end-page: 23032 ident: b0170 article-title: Low-dimensional dynamics for working memory and time encoding publication-title: Proc. Natl. Acad. Sci. – volume: 94 start-page: 978 year: 2017 end-page: 984 ident: b0150 article-title: Neural manifolds for the control of movement publication-title: Neuron – reference: J.C. Watts, et al., Serial Propagation of Distinct Strains of Aβ Prions from Alzheimer's Disease Patients. Proceedings of the National Academy of Sciences, 2014. 111 28 10323-10328. – volume: 65 start-page: 18 year: 2018 end-page: 40 ident: b0085 article-title: Abnormalities of resting-state functional cortical connectivity in patients with dementia due to alzheimer's and lewy body diseases: an EEG Study publication-title: Neurobiol. Aging – volume: 64 start-page: 631 year: 2018 end-page: 642 ident: b0015 article-title: Disease course varies according to age and symptom length in Alzheimer's Disease publication-title: J. Alzheimers Dis. – volume: 32 start-page: 127 year: 2019 end-page: 141 ident: b0090 article-title: Cortical network topology in prodromal and mild dementia due to alzheimer's disease: graph theory applied to resting state EEG publication-title: Brain Topogr. – volume: 15 start-page: 805 year: 2018 end-page: 815 ident: b0185 article-title: Inferring single-trial neural population dynamics using sequential auto-encoders publication-title: Nat. Methods – volume: 14 start-page: 43 year: 2020 ident: b0190 article-title: EEG-based emotion classification using a deep neural network and sparse autoencoder publication-title: Front. Syst. Neurosci. – volume: 74 start-page: 202 year: 2015 end-page: 210 ident: b0075 article-title: Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease publication-title: Eur. Neurol. – volume: 31 start-page: 261 year: 2005 end-page: 289 ident: b0025 article-title: Long-term effectiveness of spaced-retrieval memory training for older adults with probable Alzheimer's disease publication-title: Exp. Aging Res. – volume: 25 start-page: 1679 year: 2013 end-page: 1685 ident: b0215 article-title: Speech and Orofacial Apraxias in Alzheimer's Disease publication-title: Int. Psychogeriatr. – volume: 506 start-page: 1093 year: 2018 end-page: 1103 ident: b0100 article-title: Functional brain connectivity in alzheimer's disease: an EEG study based on permutation disalignment index publication-title: Physica. A – volume: 58 start-page: 632 year: 2017 end-page: 638 ident: b0230 article-title: 18F-Fdg pet in posterior cortical atrophy and dementia with Lewy bodies publication-title: J. Nucl. Med. – volume: 73 year: 2022 ident: 10.1016/j.bspc.2023.104917_b0125 article-title: Detection of Epileptic Seizures on EEG signals using anfis classifier, autoencoders and fuzzy entropies publication-title: Biomed. Signal Process. Control doi: 10.1016/j.bspc.2021.103417 – volume: 13 start-page: 6635 issue: 1 year: 2022 ident: 10.1016/j.bspc.2023.104917_b0040 article-title: Amyloid-associated increases in soluble Tau relate to tau aggregation rates and cognitive decline in Early Alzheimer’s disease publication-title: Nat. Commun. doi: 10.1038/s41467-022-34129-4 – volume: 25 start-page: 1679 issue: 10 year: 2013 ident: 10.1016/j.bspc.2023.104917_b0215 article-title: Speech and Orofacial Apraxias in Alzheimer's Disease publication-title: Int. Psychogeriatr. doi: 10.1017/S1041610213000781 – volume: 25 issue: 1 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0070 article-title: Multiple feature extraction and classification of electroencephalograph signal for Alzheimers' with spectrum and bispectrum. chaos: an interdisciplinary publication-title: J. Nonlinear Sci. – start-page: 5174815 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0045 article-title: Systematic review on resting-state EEG for Alzheimer's disease diagnosis and progression assessment publication-title: Dis. Markers – volume: 13 start-page: 21 issue: 1 year: 1967 ident: 10.1016/j.bspc.2023.104917_b0265 article-title: Nearest neighbor pattern classification publication-title: IEEE Trans. Inf. Theory doi: 10.1109/TIT.1967.1053964 – volume: 17 start-page: 1500 issue: 11 year: 2014 ident: 10.1016/j.bspc.2023.104917_b0180 article-title: Dimensionality reduction for large-scale neural recordings publication-title: Nat. Neurosci. doi: 10.1038/nn.3776 – volume: 85 start-page: 114 issue: 1 year: 2019 ident: 10.1016/j.bspc.2023.104917_b0010 article-title: Attributable risk of Alzheimer's dementia attributed to age-related neuropathologies publication-title: Ann. Neurol. doi: 10.1002/ana.25380 – ident: 10.1016/j.bspc.2023.104917_b0235 doi: 10.1073/pnas.2212954119 – volume: 15 start-page: 805 issue: 10 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0185 article-title: Inferring single-trial neural population dynamics using sequential auto-encoders publication-title: Nat. Methods doi: 10.1038/s41592-018-0109-9 – volume: 94 start-page: 978 issue: 5 year: 2017 ident: 10.1016/j.bspc.2023.104917_b0150 article-title: Neural manifolds for the control of movement publication-title: Neuron doi: 10.1016/j.neuron.2017.05.025 – volume: 180 start-page: 536 issue: 3 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0155 article-title: Cerebellar neurodynamics predict decision timing and outcome on the single-trial level publication-title: Cell doi: 10.1016/j.cell.2019.12.018 – volume: 29 start-page: 1557 year: 2021 ident: 10.1016/j.bspc.2023.104917_b0140 article-title: Feature extraction and identification of alzheimer's disease based on latent factor of multi-channel EEG publication-title: IEEE Trans. Neural Syst. Rehabil. Eng. doi: 10.1109/TNSRE.2021.3101240 – volume: 64 start-page: 631 issue: 2 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0015 article-title: Disease course varies according to age and symptom length in Alzheimer's Disease publication-title: J. Alzheimers Dis. doi: 10.3233/JAD-170841 – volume: 74 start-page: 58 year: 2017 ident: 10.1016/j.bspc.2023.104917_b0115 article-title: Using deep learning to investigate the neuroimaging correlates of psychiatric and neurological disorders: methods and applications publication-title: Neurosci. Biobehav. Rev. doi: 10.1016/j.neubiorev.2017.01.002 – ident: 10.1016/j.bspc.2023.104917_b0030 doi: 10.1073/pnas.1408900111 – volume: 42 start-page: 160 issue: 3 year: 2011 ident: 10.1016/j.bspc.2023.104917_b0130 article-title: Improving Alzheimer's disease diagnosis with machine learning techniques publication-title: Clin. EEG Neurosci. doi: 10.1177/155005941104200304 – volume: 38 start-page: 9390 issue: 44 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0145 article-title: Latent factors and dynamics in motor cortex and their application to brain-machine interfaces publication-title: J. Neurosci. doi: 10.1523/JNEUROSCI.1669-18.2018 – volume: 74 start-page: 202 issue: 3–4 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0075 article-title: Clinical Neurophysiological and Automated EEG-Based Diagnosis of the Alzheimer's Disease publication-title: Eur. Neurol. doi: 10.1159/000441447 – volume: 6 start-page: 7759 issue: 1 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0175 article-title: Single-trial dynamics of motor cortex and their applications to brain-machine interfaces publication-title: Nat. Commun. doi: 10.1038/ncomms8759 – volume: 72 year: 2021 ident: 10.1016/j.bspc.2023.104917_b0095 article-title: Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease publication-title: Ageing Res. Rev. doi: 10.1016/j.arr.2021.101482 – volume: 20 start-page: 222 issue: 3 year: 2021 ident: 10.1016/j.bspc.2023.104917_b0225 article-title: New insights into atypical Alzheimer's disease in the era of biomarkers publication-title: The Lancet Neurol. doi: 10.1016/S1474-4422(20)30440-3 – volume: 96 start-page: e81 issue: 1 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0220 article-title: Topographic Distribution of Amyloid-Β, Tau, and Atrophy in Patients with Behavioral/Dysexecutive Alzheimer Disease publication-title: Neurology – volume: 487 start-page: 51 issue: 7405 year: 2012 ident: 10.1016/j.bspc.2023.104917_b0160 article-title: Neural population dynamics during reaching publication-title: Nature doi: 10.1038/nature11129 – volume: 98 start-page: 1005 issue: 5 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0165 article-title: Flexible sensorimotor computations through rapid reconfiguration of cortical dynamics publication-title: Neuron doi: 10.1016/j.neuron.2018.05.020 – volume: 45 start-page: 104 issue: 2 year: 2014 ident: 10.1016/j.bspc.2023.104917_b0210 article-title: Clinician’s road map to wavelet EEG as an Alzheimer’s Disease Biomarker publication-title: Clin. EEG Neurosci. doi: 10.1177/1550059413486272 – volume: 117 start-page: 23021 issue: 37 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0170 article-title: Low-dimensional dynamics for working memory and time encoding publication-title: Proc. Natl. Acad. Sci. doi: 10.1073/pnas.1915984117 – volume: 82 start-page: 239 issue: 4 year: 1991 ident: 10.1016/j.bspc.2023.104917_b0005 article-title: Neuropathological Stageing of Alzheimer-Related Changes publication-title: Acta. Neuropathol. doi: 10.1007/BF00308809 – volume: 27 start-page: 221 issue: 3 year: 1987 ident: 10.1016/j.bspc.2023.104917_b0270 article-title: Simplifying decision trees publication-title: Int. J. Man Mach. Stud. doi: 10.1016/S0020-7373(87)80053-6 – volume: 28 start-page: 60 issue: 1 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0135 article-title: Supervised Network-Based Fuzzy Learning of EEG Signals for Alzheimer's Disease Identification publication-title: IEEE Trans. Fuzzy Syst. doi: 10.1109/TFUZZ.2019.2903753 – volume: 143 start-page: 1249 issue: 4 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0080 article-title: Network localization of clinical, cognitive, and neuropsychiatric symptoms in Alzheimer’s Disease publication-title: Brain doi: 10.1093/brain/awaa058 – volume: 14 start-page: 641 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0110 article-title: Identification of Alzheimer's EEG with a WVG Network-Based Fuzzy Learning Approach publication-title: Front. Neurosci. doi: 10.3389/fnins.2020.00641 – volume: 16 start-page: e1008128 issue: 8 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0205 article-title: Engineering recurrent neural networks from task-relevant manifolds and dynamics publication-title: PLoS Comput. Biol. doi: 10.1371/journal.pcbi.1008128 – volume: 20 start-page: 391 issue: 4 year: 2013 ident: 10.1016/j.bspc.2023.104917_b0255 article-title: EEG-based expert system using complexity measures and probability density function control in alpha sub-band publication-title: Integr. Comput.-Aided Eng. doi: 10.3233/ICA-130439 – volume: 7 start-page: 53731 year: 2019 ident: 10.1016/j.bspc.2023.104917_b0195 article-title: Spectrum Analysis of EEG Signals Using CNN to model patient's consciousness level based on anesthesiologists' experience publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2912273 – volume: 8 start-page: 1214 issue: 1 year: 2017 ident: 10.1016/j.bspc.2023.104917_b0035 article-title: Earliest accumulation of Β-Amyloid occurs within the default-mode network and concurrently affects brain connectivity publication-title: Nat. Commun. doi: 10.1038/s41467-017-01150-x – volume: 4 start-page: T332 issue: 4S_Part_10 year: 2008 ident: 10.1016/j.bspc.2023.104917_b0060 article-title: P1–388: resting-state oscillatory brain dynamics in Alzheimer's disease publication-title: Alzheimers Dement. – volume: 9 start-page: 291 issue: 3 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0245 article-title: Power spectral density and coherence analysis of alzheimer's EEG publication-title: Cogn. Neurodyn. doi: 10.1007/s11571-014-9325-x – volume: 14 start-page: 43 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0190 article-title: EEG-based emotion classification using a deep neural network and sparse autoencoder publication-title: Front. Syst. Neurosci. doi: 10.3389/fnsys.2020.00043 – start-page: 51. 14 year: 2020 ident: 10.1016/j.bspc.2023.104917_b0105 article-title: Functional integration and segregation in multiplex brain networks for Alzheimer's disease publication-title: Front. Neurosci. – volume: 506 start-page: 1093 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0100 article-title: Functional brain connectivity in alzheimer's disease: an EEG study based on permutation disalignment index publication-title: Physica. A doi: 10.1016/j.physa.2018.05.009 – volume: 31 start-page: 261 issue: 3 year: 2005 ident: 10.1016/j.bspc.2023.104917_b0025 article-title: Long-term effectiveness of spaced-retrieval memory training for older adults with probable Alzheimer's disease publication-title: Exp. Aging Res. doi: 10.1080/03610730590948186 – volume: 246 year: 2022 ident: 10.1016/j.bspc.2023.104917_b0120 article-title: A dynamic graph convolutional neural network framework reveals new insights into connectome dysfunctions in Adhd publication-title: Neuroimage doi: 10.1016/j.neuroimage.2021.118774 – volume: 9 start-page: 1735 issue: 8 year: 1997 ident: 10.1016/j.bspc.2023.104917_b0200 article-title: Long short-term memory publication-title: Neural Comput. doi: 10.1162/neco.1997.9.8.1735 – start-page: 1 year: 2021 ident: 10.1016/j.bspc.2023.104917_b0065 article-title: A review of methods of diagnosis and complexity analysis of Alzheimer's disease using EEG signals publication-title: Biomed Res. Int. – volume: 65 start-page: 18 year: 2018 ident: 10.1016/j.bspc.2023.104917_b0085 article-title: Abnormalities of resting-state functional cortical connectivity in patients with dementia due to alzheimer's and lewy body diseases: an EEG Study publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2017.12.023 – volume: 7 start-page: 487 issue: 6 year: 2010 ident: 10.1016/j.bspc.2023.104917_b0250 article-title: Diagnosis of Alzheimer's Disease from EEG Signals: where are we standing? publication-title: Curr. Alzheimer Res. doi: 10.2174/156720510792231720 – volume: 33 start-page: 1564 issue: 8 year: 2012 ident: 10.1016/j.bspc.2023.104917_b0050 article-title: Resting State fMRI in Alzheimer's Disease: beyond the default mode network publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2011.06.007 – volume: 27 start-page: 399 issue: 3 year: 2007 ident: 10.1016/j.bspc.2023.104917_b0020 article-title: Treatment strategies for the behavioral symptoms of Alzheimer's disease: focus on early pharmacologic intervention publication-title: Pharmacotherapy doi: 10.1592/phco.27.3.399 – volume: 36 start-page: 1245 issue: 3 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0055 article-title: Working Memory and Language Network Dysfunctions in Logopenic Aphasia: a Task-Free fMRI Comparison with Alzheimer's Dementia publication-title: Neurobiol. Aging doi: 10.1016/j.neurobiolaging.2014.12.013 – volume: 25 issue: 8 year: 2015 ident: 10.1016/j.bspc.2023.104917_b0240 article-title: Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy. chaos: an interdisciplinary publication-title: J. Nonlinear Sci. – volume: 58 start-page: 632 issue: 4 year: 2017 ident: 10.1016/j.bspc.2023.104917_b0230 article-title: 18F-Fdg pet in posterior cortical atrophy and dementia with Lewy bodies publication-title: J. Nucl. Med. doi: 10.2967/jnumed.116.179903 – volume: 32 start-page: 127 issue: 1 year: 2019 ident: 10.1016/j.bspc.2023.104917_b0090 article-title: Cortical network topology in prodromal and mild dementia due to alzheimer's disease: graph theory applied to resting state EEG publication-title: Brain Topogr. doi: 10.1007/s10548-018-0674-3 – volume: 20 start-page: 273 issue: 3 year: 1995 ident: 10.1016/j.bspc.2023.104917_b0260 article-title: Support-vector networks publication-title: Mach. Learn. doi: 10.1023/A:1022627411411 |
| SSID | ssj0048714 |
| Score | 2.3607574 |
| Snippet | •An automatic EEG-based diagnosis scheme for Alzheimer’s disease (AD) with deep learning methods was proposed.•A Spatial-Temporal Autoencoder (STAE) framework... |
| SourceID | crossref elsevier |
| SourceType | Enrichment Source Index Database Publisher |
| StartPage | 104917 |
| SubjectTerms | Alzheimer’s disease Deep learning Diagnosis Latent brain dynamics Spatial-Temporal Autoencoder |
| Title | Efficient identification of Alzheimer’s brain dynamics with Spatial-Temporal Autoencoder: A deep learning approach for diagnosing brain disorders |
| URI | https://dx.doi.org/10.1016/j.bspc.2023.104917 |
| Volume | 86 |
| WOSCitedRecordID | wos000986554400001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1746-8108 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0048714 issn: 1746-8094 databaseCode: AIEXJ dateStart: 20060101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3LbtNAFB2FlgUsEE-1vDQLdpEr22N7bHYRCoIKVSCCFLGxxvNoXUVO1CRVYcU_sOI_-CK-hDvPuAFVgMTGikaeseVzMvfOzL3nIvRMUnCLwbRFPKYsAnutoqpqmkgSnhWSM1HkwhSboEdH5XRavR0MvvtcmPMZ7bry4qJa_FeooQ3A1qmzfwF3GBQa4DeADleAHa5_BPzYiELoI_5WuFCg4BaOZp9PZKsLprgYh2o5bHSRiKGwleldspsuVAxvGk2scBWguF7NteSllhsxuexCyoUvOXEclMlN0KKw0Xu63Y3tFD6Xl06QTd6_Tcpsj7VPvLA5Cz5r0gXRB6uxdlsIx5_WgdAfT5jZ6n23Zp0KBuZNa-499FbZ1B0zNpa1Kzbvb3SkJERyud03n4GzCXfSEzbNtKCyLZR8IHttSVz2Z3kruP2LwbB7F6cHzXKhBS1Tog-9K5tOuiXE_V6Pqx8FqzZ9HltcQ7spzSuYS3dHr8fTQ-8BwBrQaMqHd3PJWjaucPtJv3eIek7O5Da65VYneGRZdQcNZHcX3expVt5DXwO_8GV-4bnCgV8_vnxbYoM-9szCmll4m1m4x6zneIQ1r7DnFfa8wsArvOGVH9nz6j768HI8efEqcpU9Ig7fbhURLkTCMlZywhT42OAkE54wWSoal4xWaUFJmgiaszgpi0w1TU5UUwkSN3Ghmpg8QDvdvJN7COecKE5LGZOGZUqkVUoVh4FlRgXY8WIfJf7z1tzJ3uvqK7Paxzee1hqSWkNSW0j20TD0WVjRlyvvzj1qtXNbrTtaA8mu6PfwH_s9Qjc2f4_HaGd1tpZP0HV-vmqXZ08dF38CQFHDmw |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Efficient+identification+of+Alzheimer%E2%80%99s+brain+dynamics+with+Spatial-Temporal+Autoencoder%3A+A+deep+learning+approach+for+diagnosing+brain+disorders&rft.jtitle=Biomedical+signal+processing+and+control&rft.au=Wu%2C+Lingyun&rft.au=Zhao%2C+Quanfa&rft.au=Liu%2C+Jing&rft.au=Yu%2C+Haitao&rft.date=2023-09-01&rft.pub=Elsevier+Ltd&rft.issn=1746-8094&rft.eissn=1746-8108&rft.volume=86&rft_id=info:doi/10.1016%2Fj.bspc.2023.104917&rft.externalDocID=S1746809423003506 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1746-8094&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1746-8094&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1746-8094&client=summon |