{"id":"https://openalex.org/W4415765585","doi":"https://doi.org/10.1016/j.compbiomed.2025.111261","title":"Taming diffusion transformers for high-fidelity MRI super-resolution","display_name":"Taming diffusion transformers for high-fidelity MRI super-resolution","publication_year":2025,"publication_date":"2025-11-01","ids":{"openalex":"https://openalex.org/W4415765585","doi":"https://doi.org/10.1016/j.compbiomed.2025.111261","pmid":"https://pubmed.ncbi.nlm.nih.gov/41176825"},"language":"en","primary_location":{"id":"doi:10.1016/j.compbiomed.2025.111261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.111261","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.compbiomed.2025.111261","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104314381","display_name":"Xinyue Tu","orcid":"https://orcid.org/0009-0001-3540-6532"},"institutions":[{"id":"https://openalex.org/I4210166576","display_name":"First Affiliated Hospital Zhejiang University","ror":"https://ror.org/05m1p5x56","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210166576"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyue Tu","raw_affiliation_strings":["Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China"],"raw_orcid":"https://orcid.org/0009-0001-3540-6532","affiliations":[{"raw_affiliation_string":"Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China","institution_ids":["https://openalex.org/I4210166576"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101603720","display_name":"Guangyuan Li","orcid":"https://orcid.org/0000-0002-2938-527X"},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangyuan Li","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China"],"raw_orcid":"https://orcid.org/0000-0002-2938-527X","affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University, Hangzhou, 310027, China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101442943","display_name":"Zhongwen Fan","orcid":"https://orcid.org/0009-0009-6253-6613"},"institutions":[{"id":"https://openalex.org/I4210166576","display_name":"First Affiliated Hospital Zhejiang University","ror":"https://ror.org/05m1p5x56","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210166576"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongwen Fan","raw_affiliation_strings":["Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China"],"raw_orcid":"https://orcid.org/0009-0009-6253-6613","affiliations":[{"raw_affiliation_string":"Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China","institution_ids":["https://openalex.org/I4210166576"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xinjiang Ding","orcid":"https://orcid.org/0000-0002-2289-8072"},"institutions":[{"id":"https://openalex.org/I4210166576","display_name":"First Affiliated Hospital Zhejiang University","ror":"https://ror.org/05m1p5x56","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210166576"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjiang Ding","raw_affiliation_strings":["Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China"],"raw_orcid":"https://orcid.org/0000-0002-2289-8072","affiliations":[{"raw_affiliation_string":"Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China","institution_ids":["https://openalex.org/I4210166576"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yuanxing Liu","orcid":"https://orcid.org/0000-0002-9950-991X"},"institutions":[{"id":"https://openalex.org/I4210166576","display_name":"First Affiliated Hospital Zhejiang University","ror":"https://ror.org/05m1p5x56","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210166576"]},{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanxing Liu","raw_affiliation_strings":["Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. Electronic address: liuyuanxing@zju.edu.cn"],"raw_orcid":"https://orcid.org/0000-0002-9950-991X","affiliations":[{"raw_affiliation_string":"Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China. Electronic address: liuyuanxing@zju.edu.cn","institution_ids":["https://openalex.org/I4210166576","https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5104314381"],"corresponding_institution_ids":["https://openalex.org/I4210166576"],"apc_list":{"value":2610,"currency":"USD","value_usd":2610},"apc_paid":{"value":2610,"currency":"USD","value_usd":2610},"fwci":1.1332,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83789633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"198","issue":"Pt B","first_page":"111261","last_page":"111261"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3700000047683716,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.3700000047683716,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.35679998993873596,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.1362999975681305,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6597999930381775},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.592199981212616},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5491999983787537},{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.4336000084877014},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41819998621940613},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.3977000117301941},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.38199999928474426},{"id":"https://openalex.org/keywords/feed-forward","display_name":"Feed forward","score":0.3725000023841858},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.33480000495910645}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7626000046730042},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6597999930381775},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.592199981212616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5877000093460083},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5491999983787537},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.4336000084877014},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41819998621940613},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4025000035762787},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C38858127","wikidata":"https://www.wikidata.org/wiki/Q5441228","display_name":"Feed forward","level":2,"score":0.3725000023841858},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.30720001459121704},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.28999999165534973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2883000075817108},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C157787499","wikidata":"https://www.wikidata.org/wiki/Q13479657","display_name":"Real-time MRI","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.2703999876976013},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.25119999051094055},{"id":"https://openalex.org/C3017601658","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image enhancement","level":3,"score":0.25119999051094055}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":"Q000000981","qualifier_name":"diagnostic imaging","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D007091","descriptor_name":"Image Processing, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true},{"descriptor_ui":"D008279","descriptor_name":"Magnetic Resonance Imaging","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1016/j.compbiomed.2025.111261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.111261","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},{"id":"pmid:41176825","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41176825","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in biology and medicine","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.compbiomed.2025.111261","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.compbiomed.2025.111261","pdf_url":null,"source":{"id":"https://openalex.org/S44278595","display_name":"Computers in Biology and Medicine","issn_l":"0010-4825","issn":["0010-4825","1879-0534"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computers in Biology and Medicine","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2083343359","display_name":null,"funder_award_id":"LZ24H030001","funder_id":"https://openalex.org/F4320338464","funder_display_name":"Natural Science Foundation of Zhejiang Province"},{"id":"https://openalex.org/G2251898864","display_name":null,"funder_award_id":"81970543","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320338464","display_name":"Natural Science Foundation of Zhejiang Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2966737464","https://openalex.org/W3032400974","https://openalex.org/W3092755853","https://openalex.org/W3134103558","https://openalex.org/W3179253672","https://openalex.org/W3183394902","https://openalex.org/W3202223141","https://openalex.org/W3205399766","https://openalex.org/W4296057623","https://openalex.org/W4312233661","https://openalex.org/W4312933868","https://openalex.org/W4381332772","https://openalex.org/W4382372079","https://openalex.org/W4385272245","https://openalex.org/W4386047807","https://openalex.org/W4390872297","https://openalex.org/W4390873327","https://openalex.org/W4390873332","https://openalex.org/W4390873495","https://openalex.org/W4390893614","https://openalex.org/W4402753589","https://openalex.org/W4402753813","https://openalex.org/W4402904179","https://openalex.org/W4404404925","https://openalex.org/W4405908078","https://openalex.org/W4408384439","https://openalex.org/W4408588410","https://openalex.org/W4409346369","https://openalex.org/W4413146346","https://openalex.org/W4413146579","https://openalex.org/W4413883630"],"related_works":[],"abstract_inverted_index":{"Recent":[0],"MRI":[1,107,147],"super-resolution":[2],"(SR)":[3],"methods":[4,35],"increasingly":[5],"adopt":[6],"diffusion":[7,30,87],"models":[8,31,88],"to":[9,77,126,170,217,238],"enhance":[10],"reconstruction":[11],"quality.":[12],"While":[13],"these":[14,34,139,183],"approaches":[15],"have":[16],"achieved":[17],"promising":[18],"improvements":[19],"in":[20,33,46,92,103,119],"image":[21],"quality,":[22],"they":[23,100,110],"still":[24],"face":[25],"two":[26,194],"challenges.":[27],"First,":[28],"the":[29,69,104,120,133,143],"employed":[32],"are":[36,60],"typically":[37],"constructed":[38],"upon":[39],"U-Net":[40,43,70],"architectures.":[41],"Although":[42],"offers":[44],"advantages":[45],"capturing":[47],"local":[48],"structures,":[49],"it":[50,124],"struggles":[51,76],"with":[52,80],"modeling":[53],"global":[54,93],"context":[55,105],"and":[56,75,95,115,149,205,214,221,228],"long-range":[57],"dependencies,":[58],"which":[59],"essential":[61],"for":[62,146],"faithfully":[63],"recovering":[64],"complex":[65,81],"anatomical":[66,82],"details.":[67],"Moreover,":[68],"architecture":[71],"exhibits":[72],"limited":[73],"scalability":[74],"handle":[78],"images":[79,131,181],"structures.":[83],"In":[84],"contrast,":[85],"Transformer-based":[86],"exhibit":[89],"stronger":[90],"capabilities":[91],"reasoning":[94],"multi-scale":[96],"dependency":[97],"modeling,":[98],"yet":[99],"remain":[101],"underexplored":[102],"of":[106,193],"super-resolution.":[108],"Second,":[109],"often":[111],"lack":[112],"a":[113,151,159,166,188,197,206,211],"powerful":[114],"efficient":[116],"decoding":[117,219],"mechanism":[118],"latent":[121,135,168,175,184],"space,":[122],"making":[123],"difficult":[125],"accurately":[127],"reconstruct":[128,178],"high-fidelity":[129,179],"MR":[130,174,180],"from":[132,182],"generated":[134],"representations.":[136],"To":[137,177],"address":[138],"challenges,":[140],"we":[141,157,186],"tame":[142],"Diffusion":[144,161],"Transformer":[145,162],"super-resolution,":[148],"propose":[150],"novel":[152],"framework":[153],"called":[154],"DiTMSR.":[155],"Specifically,":[156],"design":[158,187],"conditional":[160],"that":[163,201,232],"progressively":[164],"denoises":[165],"noisy":[167],"input":[169],"recover":[171],"structurally":[172],"faithful":[173],"features.":[176],"features,":[185],"hybrid":[189,207],"Mamba":[190,208],"decoder":[191],"consisting":[192],"key":[195],"components:":[196],"content":[198],"preservation":[199],"module":[200],"retains":[202],"structural":[203],"information,":[204],"block":[209],"combining":[210],"MambaVision":[212],"Mixer":[213],"feedforward":[215],"network":[216],"improve":[218],"performance":[220,236],"efficiency.":[222],"Extensive":[223],"experiments":[224],"on":[225],"both":[226],"public":[227],"clinical":[229],"datasets":[230],"demonstrate":[231],"DiTMSR":[233],"achieves":[234],"superior":[235],"compared":[237],"state-of-the-art":[239],"methods.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-11-01T00:00:00"}