{"id":"https://openalex.org/W3005368325","doi":"https://doi.org/10.1109/tim.2020.2972172","title":"Time Sequence Learning for Electrical Impedance Tomography Using Bayesian Spatiotemporal Priors","display_name":"Time Sequence Learning for Electrical Impedance Tomography Using Bayesian Spatiotemporal Priors","publication_year":2020,"publication_date":"2020-02-06","ids":{"openalex":"https://openalex.org/W3005368325","doi":"https://doi.org/10.1109/tim.2020.2972172","mag":"3005368325"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2020.2972172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2972172","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.research.ed.ac.uk/files/134845484/Efficient_multi_task_structure_aware_sparse_Bayesian_learning_for_frequency_difference_electrical_impedance_tomography.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053773849","display_name":"Shengheng Liu","orcid":"https://orcid.org/0000-0001-6579-9798"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengheng Liu","raw_affiliation_strings":["School of Information Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6579-9798","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014533194","display_name":"Ruisong Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruisong Cao","raw_affiliation_strings":["School of Information Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-8602-4385","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056225611","display_name":"Yongming Huang","orcid":"https://orcid.org/0000-0003-3616-4616"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongming Huang","raw_affiliation_strings":["School of Information Science and Engineering, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-3616-4616","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042356469","display_name":"Taweechai Ouypornkochagorn","orcid":"https://orcid.org/0000-0003-3451-7123"},"institutions":[{"id":"https://openalex.org/I76920116","display_name":"Srinakharinwirot University","ror":"https://ror.org/04718hx42","country_code":"TH","type":"education","lineage":["https://openalex.org/I76920116"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Taweechai Ouypornkochagorn","raw_affiliation_strings":["Department of Biomedical Engineering, Srinakharinwirot University, Bangkok, Thailand","Srinakharinwirot University, Bangkok, Thailand"],"raw_orcid":"https://orcid.org/0000-0003-3451-7123","affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, Srinakharinwirot University, Bangkok, Thailand","institution_ids":["https://openalex.org/I76920116"]},{"raw_affiliation_string":"Srinakharinwirot University, Bangkok, Thailand","institution_ids":["https://openalex.org/I76920116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113057002","display_name":"Jiabin Ji","orcid":null},"institutions":[{"id":"https://openalex.org/I98677209","display_name":"University of Edinburgh","ror":"https://ror.org/01nrxwf90","country_code":"GB","type":"education","lineage":["https://openalex.org/I98677209"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jiabin Jia","raw_affiliation_strings":["Agile Tomography Group, School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, U.K"],"raw_orcid":"https://orcid.org/0000-0001-5073-5126","affiliations":[{"raw_affiliation_string":"Agile Tomography Group, School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, U.K","institution_ids":["https://openalex.org/I98677209"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.2331,"has_fulltext":true,"cited_by_count":81,"citation_normalized_percentile":{"value":0.9521711,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"69","issue":"9","first_page":"6045","last_page":"6057"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11778","display_name":"Electrical and Bioimpedance Tomography","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12537","display_name":"Flow Measurement and Analysis","score":0.994700014591217,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10572","display_name":"Geophysical and Geoelectrical Methods","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.7592790722846985},{"id":"https://openalex.org/keywords/electrical-impedance-tomography","display_name":"Electrical impedance tomography","score":0.6876273155212402},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.622070848941803},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5589472651481628},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.5235198140144348},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5215218663215637},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.47753918170928955},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.46808961033821106},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4617471992969513},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44691145420074463},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21926549077033997},{"id":"https://openalex.org/keywords/electrical-impedance","display_name":"Electrical impedance","score":0.20340079069137573},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09379705786705017}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7592790722846985},{"id":"https://openalex.org/C155175808","wikidata":"https://www.wikidata.org/wiki/Q1326472","display_name":"Electrical impedance tomography","level":3,"score":0.6876273155212402},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.622070848941803},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5589472651481628},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.5235198140144348},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5215218663215637},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.47753918170928955},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.46808961033821106},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4617471992969513},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44691145420074463},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21926549077033997},{"id":"https://openalex.org/C17829176","wikidata":"https://www.wikidata.org/wiki/Q179043","display_name":"Electrical impedance","level":2,"score":0.20340079069137573},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09379705786705017},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tim.2020.2972172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2020.2972172","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:pure.ed.ac.uk:openaire/7d77f196-fecd-4dd4-a731-a354becd84b9","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/7d77f196-fecd-4dd4-a731-a354becd84b9","pdf_url":"https://www.research.ed.ac.uk/files/134845484/Efficient_multi_task_structure_aware_sparse_Bayesian_learning_for_frequency_difference_electrical_impedance_tomography.pdf","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Liu, S, Cao, R, Huang, Y, Ouypornkochagorn, T & Jia, J 2020, 'Time sequence learning for electrical impedance tomography using Bayesian spatiotemporal priors', IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2020.2972172","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:pure.ed.ac.uk:publications/7d77f196-fecd-4dd4-a731-a354becd84b9","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.11820/7d77f196-fecd-4dd4-a731-a354becd84b9","pdf_url":"https://www.pure.ed.ac.uk/ws/files/134845484/Efficient_multi_task_structure_aware_sparse_Bayesian_learning_for_frequency_difference_electrical_impedance_tomography.pdf","source":{"id":"https://openalex.org/S4406922455","display_name":"Edinburgh Research Explorer","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""}],"best_oa_location":{"id":"pmh:oai:pure.ed.ac.uk:openaire/7d77f196-fecd-4dd4-a731-a354becd84b9","is_oa":true,"landing_page_url":"https://www.research.ed.ac.uk/en/publications/7d77f196-fecd-4dd4-a731-a354becd84b9","pdf_url":"https://www.research.ed.ac.uk/files/134845484/Efficient_multi_task_structure_aware_sparse_Bayesian_learning_for_frequency_difference_electrical_impedance_tomography.pdf","source":{"id":"https://openalex.org/S4306400321","display_name":"Edinburgh Research Explorer (University of Edinburgh)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I98677209","host_organization_name":"University of Edinburgh","host_organization_lineage":["https://openalex.org/I98677209"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"Liu, S, Cao, R, Huang, Y, Ouypornkochagorn, T & Jia, J 2020, 'Time sequence learning for electrical impedance tomography using Bayesian spatiotemporal priors', IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2020.2972172","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5099999904632568}],"awards":[{"id":"https://openalex.org/G3092627289","display_name":"Cerebral Blood Flow Imaging based on 3D Electrical Impedance Tomography","funder_award_id":"EP/P006833/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G4465478400","display_name":null,"funder_award_id":"SBK2019042353","funder_id":"https://openalex.org/F4320334982","funder_display_name":"Basic Research Program of Jiangsu Province"},{"id":"https://openalex.org/G745719754","display_name":null,"funder_award_id":"EP/P001661/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G780682132","display_name":null,"funder_award_id":"EP/P006833/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"},{"id":"https://openalex.org/G8314740275","display_name":null,"funder_award_id":"EP/L01890X/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"},{"id":"https://openalex.org/F4320334982","display_name":"Basic Research Program of Jiangsu Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3005368325.pdf","grobid_xml":"https://content.openalex.org/works/W3005368325.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1968334032","https://openalex.org/W1974718273","https://openalex.org/W1979931789","https://openalex.org/W1991147865","https://openalex.org/W2009831994","https://openalex.org/W2021137578","https://openalex.org/W2025950086","https://openalex.org/W2034658223","https://openalex.org/W2042466299","https://openalex.org/W2056132468","https://openalex.org/W2070738097","https://openalex.org/W2071943116","https://openalex.org/W2093495347","https://openalex.org/W2100203145","https://openalex.org/W2103520741","https://openalex.org/W2111805630","https://openalex.org/W2113761410","https://openalex.org/W2127943724","https://openalex.org/W2137425275","https://openalex.org/W2141002303","https://openalex.org/W2149498546","https://openalex.org/W2156062145","https://openalex.org/W2162409952","https://openalex.org/W2169326247","https://openalex.org/W2220809057","https://openalex.org/W2237317482","https://openalex.org/W2405817978","https://openalex.org/W2575872241","https://openalex.org/W2732126315","https://openalex.org/W2735205850","https://openalex.org/W2735337215","https://openalex.org/W2751486549","https://openalex.org/W2783469501","https://openalex.org/W2785899288","https://openalex.org/W2795198316","https://openalex.org/W2801641166","https://openalex.org/W2804766665","https://openalex.org/W2883561321","https://openalex.org/W2888659593","https://openalex.org/W2896048271","https://openalex.org/W2900513822","https://openalex.org/W2901111678","https://openalex.org/W2905450017","https://openalex.org/W2910732135","https://openalex.org/W2913384339","https://openalex.org/W2916125097","https://openalex.org/W2942128991","https://openalex.org/W2942144263","https://openalex.org/W2956685331","https://openalex.org/W2963231761","https://openalex.org/W2963570578","https://openalex.org/W2964232913","https://openalex.org/W2978671283","https://openalex.org/W2990050904","https://openalex.org/W2999516274","https://openalex.org/W3102948137","https://openalex.org/W3104882764","https://openalex.org/W6761851459","https://openalex.org/W6768014465"],"related_works":["https://openalex.org/W3211685995","https://openalex.org/W2532315310","https://openalex.org/W2902419700","https://openalex.org/W3160616384","https://openalex.org/W2098962200","https://openalex.org/W2905540725","https://openalex.org/W4376629886","https://openalex.org/W2000128178","https://openalex.org/W2101428392","https://openalex.org/W2725829804"],"abstract_inverted_index":{"As":[0],"an":[1,92],"emerging":[2],"technology":[3],"for":[4,62],"continuous":[5],"monitoring":[6],"of":[7,43,73,143],"a":[8,54],"bounded":[9],"domain,":[10],"electrical":[11],"impedance":[12,46],"tomography":[13],"(EIT)":[14],"gains":[15],"increasing":[16],"popularity":[17],"in":[18,70,91],"various":[19],"applications.":[20],"Despite":[21],"unprecedented":[22],"progress,":[23],"the":[24,29,44,64,71,75,97,113,118,132,137,155,163,167,171],"EIT":[25,66,76],"inverse":[26,67],"solvers":[27],"at":[28,177],"present":[30],"stage":[31],"are":[32,87,174],"incompetent":[33],"to":[34,111,136,162,185],"guarantee":[35],"sufficient":[36],"fidelity":[37],"as":[38,40],"well":[39],"efficient":[41],"investigation":[42],"internal":[45],"dynamics.":[47],"In":[48],"this":[49,51],"context,":[50],"article":[52],"introduces":[53],"spatiotemporal":[55,114],"structure-aware":[56,102],"sparse":[57],"Bayesian":[58,99],"learning":[59],"(SA-SBL)":[60],"framework":[61],"solving":[63],"time-continuous":[65],"problems.":[68],"Specifically,":[69],"process":[72],"reconstructing":[74],"time":[77],"sequence,":[78],"both":[79],"intraframe":[80],"spatial":[81],"clustering":[82],"and":[83,89,101,116,195],"interframe":[84],"temporal":[85],"continuity":[86],"explored":[88],"exploited":[90],"unsupervised":[93],"manner":[94],"by":[95,130,170,176],"using":[96],"hierarchical":[98],"model":[100,108],"priors.":[103],"A":[104,140],"multiple":[105],"measurement":[106],"vector":[107],"is":[109,127,145,183],"established":[110],"capture":[112],"correlations":[115],"describe":[117],"underlying":[119],"multidimensional":[120],"reconstruction":[121,160],"problem.":[122],"The":[123,180],"resultant":[124],"largescale":[125],"inversion":[126],"efficiently":[128],"solved":[129],"applying":[131],"approximate":[133],"message":[134],"passing":[135],"expectation":[138],"updating.":[139],"speedup":[141],"ratio":[142],"O(N2/M)":[144],"achieved":[146],"compared":[147],"with":[148],"original":[149],"SA-SBL.":[150],"Simulation":[151],"results":[152],"indicate":[153],"that":[154],"proposed":[156],"algorithm":[157,182],"exhibits":[158],"superior":[159],"performance":[161],"existing":[164],"methods,":[165],"where":[166],"scores":[168],"evaluated":[169],"quantitative":[172],"metrics":[173],"improved":[175,192],"least":[178],"17%.":[179],"presented":[181],"envisioned":[184],"offer":[186],"broader":[187],"applicability":[188],"since":[189],"it":[190],"yields":[191],"image":[193],"quality":[194],"recovery":[196],"efficiency.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":9}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}
