{"id":"https://openalex.org/W7077054708","doi":"https://doi.org/10.1177/18724981251335096","title":"Deep learning-based analysis of functional MRI and diffusion tensor imaging for Parkinson's disease diagnosis and progression monitoring","display_name":"Deep learning-based analysis of functional MRI and diffusion tensor imaging for Parkinson's disease diagnosis and progression monitoring","publication_year":2025,"publication_date":"2025-07-01","ids":{"openalex":"https://openalex.org/W7077054708","doi":"https://doi.org/10.1177/18724981251335096"},"language":"en","primary_location":{"id":"doi:10.1177/18724981251335096","is_oa":false,"landing_page_url":"https://doi.org/10.1177/18724981251335096","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://repository.londonmet.ac.uk/10417/1/BV_Deep-learning-based-analysis_2025.08.14.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Tarak Hussain","orcid":"https://orcid.org/0000-0001-9914-1919"},"institutions":[{"id":"https://openalex.org/I126193024","display_name":"London Metropolitan University","ror":"https://ror.org/00ae33288","country_code":"GB","type":"education","lineage":["https://openalex.org/I126193024"]},{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["GB","IN"],"is_corresponding":true,"raw_author_name":"Tarak Hussain","raw_affiliation_strings":["Department of Artificial Intelligence &amp; Data Science, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India","School of Computing &amp; Digital Media, London Metropolitan University, England UK"],"raw_orcid":"https://orcid.org/0000-0001-9914-1919","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence &amp; Data Science, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India","institution_ids":["https://openalex.org/I875944469"]},{"raw_affiliation_string":"School of Computing &amp; Digital Media, London Metropolitan University, England UK","institution_ids":["https://openalex.org/I126193024"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ashish Khanna","orcid":null},"institutions":[{"id":"https://openalex.org/I2799452066","display_name":"Maharaja Engineering College","ror":"https://ror.org/034pbde03","country_code":"IN","type":"education","lineage":["https://openalex.org/I2799452066","https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ashish Khanna","raw_affiliation_strings":["Maharaja Agrasen Institute of Technology, Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maharaja Agrasen Institute of Technology, Delhi, India","institution_ids":["https://openalex.org/I2799452066"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Bal Virdee","orcid":"https://orcid.org/0000-0001-7203-0039"},"institutions":[{"id":"https://openalex.org/I126193024","display_name":"London Metropolitan University","ror":"https://ror.org/00ae33288","country_code":"GB","type":"education","lineage":["https://openalex.org/I126193024"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Bal Virdee","raw_affiliation_strings":["Centre for Communication Technology, London Metropolitan University, England UK"],"raw_orcid":"https://orcid.org/0000-0001-7203-0039","affiliations":[{"raw_affiliation_string":"Centre for Communication Technology, London Metropolitan University, England UK","institution_ids":["https://openalex.org/I126193024"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Kunchanapaalli Rama Krishna","orcid":"https://orcid.org/0000-0001-9393-7713"},"institutions":[{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kunchanapaalli Rama Krishna","raw_affiliation_strings":["Department of CSIT, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India"],"raw_orcid":"https://orcid.org/0000-0001-9393-7713","affiliations":[{"raw_affiliation_string":"Department of CSIT, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India","institution_ids":["https://openalex.org/I875944469"]}]},{"author_position":"last","author":{"id":null,"display_name":"JVS Arundathi","orcid":null},"institutions":[{"id":"https://openalex.org/I875944469","display_name":"Koneru Lakshmaiah Education Foundation","ror":"https://ror.org/02k949197","country_code":"IN","type":"education","lineage":["https://openalex.org/I875944469"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"JVS Arundathi","raw_affiliation_strings":["Department of Artificial Intelligence &amp; Data Science, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence &amp; Data Science, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India","institution_ids":["https://openalex.org/I875944469"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I126193024","https://openalex.org/I875944469"],"apc_list":null,"apc_paid":null,"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87750365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"19","issue":"4","first_page":"2196","last_page":"2211"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6233999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6233999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13067","display_name":"Geological Modeling and Analysis","score":0.02800000086426735,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14311","display_name":"Electrical and Electromagnetic Research","score":0.023600000888109207,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/diffusion-mri","display_name":"Diffusion MRI","score":0.7350000143051147},{"id":"https://openalex.org/keywords/neuroimaging","display_name":"Neuroimaging","score":0.7239000201225281},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6453999876976013},{"id":"https://openalex.org/keywords/white-matter","display_name":"White matter","score":0.607699990272522},{"id":"https://openalex.org/keywords/magnetic-resonance-imaging","display_name":"Magnetic resonance imaging","score":0.4846000075340271},{"id":"https://openalex.org/keywords/functional-magnetic-resonance-imaging","display_name":"Functional magnetic resonance imaging","score":0.4269999861717224}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7696999907493591},{"id":"https://openalex.org/C149550507","wikidata":"https://www.wikidata.org/wiki/Q899360","display_name":"Diffusion MRI","level":3,"score":0.7350000143051147},{"id":"https://openalex.org/C58693492","wikidata":"https://www.wikidata.org/wiki/Q551875","display_name":"Neuroimaging","level":2,"score":0.7239000201225281},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6453999876976013},{"id":"https://openalex.org/C2781192897","wikidata":"https://www.wikidata.org/wiki/Q822050","display_name":"White matter","level":3,"score":0.607699990272522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5052000284194946},{"id":"https://openalex.org/C143409427","wikidata":"https://www.wikidata.org/wiki/Q161238","display_name":"Magnetic resonance imaging","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48240000009536743},{"id":"https://openalex.org/C2779226451","wikidata":"https://www.wikidata.org/wiki/Q903809","display_name":"Functional magnetic resonance imaging","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41339999437332153},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4011000096797943},{"id":"https://openalex.org/C89916169","wikidata":"https://www.wikidata.org/wiki/Q17014600","display_name":"Fractional anisotropy","level":4,"score":0.35899999737739563},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.305400013923645},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.3027999997138977},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.29499998688697815},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2653999924659729}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1177/18724981251335096","is_oa":false,"landing_page_url":"https://doi.org/10.1177/18724981251335096","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"},{"id":"pmh:oai:repository.londonmet.ac.uk:10417","is_oa":true,"landing_page_url":null,"pdf_url":"https://repository.londonmet.ac.uk/10417/1/BV_Deep-learning-based-analysis_2025.08.14.pdf","source":{"id":"https://openalex.org/S4306400140","display_name":"London Met Repository (London Metropolitan University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126193024","host_organization_name":"London Metropolitan University","host_organization_lineage":["https://openalex.org/I126193024"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:repository.londonmet.ac.uk:10417","is_oa":true,"landing_page_url":null,"pdf_url":"https://repository.londonmet.ac.uk/10417/1/BV_Deep-learning-based-analysis_2025.08.14.pdf","source":{"id":"https://openalex.org/S4306400140","display_name":"London Met Repository (London Metropolitan University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I126193024","host_organization_name":"London Metropolitan University","host_organization_lineage":["https://openalex.org/I126193024"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W7077054708.pdf"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W3121484310","https://openalex.org/W3151314054","https://openalex.org/W3161550737","https://openalex.org/W4213315779","https://openalex.org/W4214910749","https://openalex.org/W4221093457","https://openalex.org/W4281833320","https://openalex.org/W4292179101","https://openalex.org/W4294225910","https://openalex.org/W4323568500","https://openalex.org/W4366134159","https://openalex.org/W4367595499","https://openalex.org/W4379874904","https://openalex.org/W4381249043","https://openalex.org/W4392154382","https://openalex.org/W4393282281","https://openalex.org/W4396778892","https://openalex.org/W4399984148","https://openalex.org/W4401977390"],"related_works":[],"abstract_inverted_index":{"Parkinson's":[0],"Disease":[1],"(PD)":[2],"refers":[3],"to":[4,47,67,89,95,114,128,140,175,241],"the":[5,11,14,50,76,79,91,96,106,110,116,121,129,142,165,168,176,180,183,189,197,209,264,267,279,287,296,304,310,313],"chronic":[6],"movement":[7],"disorder":[8],"caused":[9],"by":[10],"degeneration":[12],"of":[13,43,63,78,83,167,182,199,233,266,281,289,299,306,312],"brain's":[15],"motor":[16],"functions.":[17],"Functional":[18],"Magnetic":[19],"Resonance":[20],"Imaging":[21,26],"(fMRI)":[22],"and":[23,36,65,74,109,145,159,171,173,192,202,244,249,283,292,309,317],"Diffusion":[24],"Tensor":[25],"(DTI)":[27],"are":[28,86],"evidence-based":[29],"neuroimaging":[30,143],"procedures":[31],"which":[32],"evoke":[33],"relevant":[34],"anatomical":[35],"functional":[37],"alterations":[38],"in":[39,120,225,254,286],"PD.":[40],"The":[41,81,134],"purpose":[42],"this":[44,84],"work":[45,269,301],"is":[46,126,137],"investigate":[48],"whether":[49],"machine":[51,177,218],"learning":[52,59,103,154,178,213,219,276],"approach":[53,136],"can":[54,270],"benefit":[55],"from":[56,105,164],"applying":[57],"deep":[58,102,153,212,275],"for":[60,93,227,273,278],"data":[61,108,138,144,285],"interpretation":[62],"fMRI":[64,107,282],"DTI":[66,132,284],"detect":[68],"disease":[69],"at":[70],"an":[71],"early":[72],"stage":[73],"study":[75],"progression":[77],"disease.":[80],"objectives":[82],"research":[85],"twofold:":[87],"first,":[88],"predict":[90],"biomarkers":[92],"attending":[94],"changed":[97],"brain":[98,247],"activity":[99],"pattern":[100],"using":[101,131,152,188],"model":[104],"second":[111],"one":[112],"is,":[113],"find":[115],"micro":[117],"structural":[118],"changes":[119],"white":[122,250],"matter":[123,251],"tracts":[124,252],"that":[125,208],"specific":[127],"PD":[130,169,200,229,242,290],"data.":[133],"adopted":[135],"pre-processing":[139],"clean":[141],"remove":[146],"different":[147],"artifacts,":[148],"then":[149],"features":[150,239],"extraction":[151],"approaches":[155],"such":[156],"as":[157],"CNNs":[158],"transformers.":[160],"Data":[161],"were":[162],"collected":[163],"intersection":[166],"patients":[170,201],"controls,":[172],"similar":[174],"models,":[179],"performance":[181],"segmentation":[184],"models":[185,214,314],"was":[186],"assessed":[187],"accuracy,":[190],"precision,":[191],"F1":[193],"score":[194],"based":[195],"on":[196,315],"databases":[198],"age-matched":[203],"healthy":[204],"controls.":[205],"Analysis":[206],"shows":[207],"newly":[210],"developed":[211],"outperforms":[215],"previous":[216],"conventional":[217],"techniques":[220],"with":[221,257],"more":[222,318],"significant":[223,237],"increases":[224],"sensitivity":[226],"early-stage":[228],"diagnosis.":[230],"Respective":[231],"investigation":[232],"feature":[234],"importance":[235],"provided":[236],"BrainNet":[238],"related":[240],"diagnosis":[243,291],"identified":[245],"main":[246],"areas":[248],"involved":[253],"disease,":[255],"concordant":[256],"prior":[258],"clinical":[259],"research.":[260,294],"To":[261],"sum":[262],"up,":[263],"findings":[265],"presented":[268],"be":[271],"useful":[272],"developing":[274],"algorithms":[277],"analysis":[280],"context":[288],"further":[293],"Lastly,":[295],"general":[297],"avenue":[298],"future":[300],"will":[302],"cover":[303],"combination":[305],"multiple":[307],"modalities":[308],"testing":[311],"bigger":[316],"diverse":[319],"datasets.":[320]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
