{"id":"https://openalex.org/W4408941356","doi":"https://doi.org/10.1109/access.2025.3555767","title":"Detecting Throat Cancer From Speech Signals Using Machine Learning: A Scoping Literature Review","display_name":"Detecting Throat Cancer From Speech Signals Using Machine Learning: A Scoping Literature Review","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4408941356","doi":"https://doi.org/10.1109/access.2025.3555767"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3555767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3555767","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3555767","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103026741","display_name":"Mary Paterson","orcid":"https://orcid.org/0009-0004-9144-0438"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mary Paterson","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, U.K","Faculty of Engineering and Physical Sciences University of Leeds, Leeds, UK"],"raw_orcid":"https://orcid.org/0009-0004-9144-0438","affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]},{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences University of Leeds, Leeds, UK","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083489504","display_name":"James Moor","orcid":"https://orcid.org/0000-0002-4399-0572"},"institutions":[{"id":"https://openalex.org/I2799390153","display_name":"Leeds Teaching Hospitals NHS Trust","ror":"https://ror.org/00v4dac24","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I2799390153"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Moor","raw_affiliation_strings":["Ear, Nose and Throat Department, Leeds Teaching Hospitals NHS Trust, Leeds, U.K","Ear, Nose and Throat Department Leeds Teaching Hospitals NHS Trust, Leeds, UK"],"raw_orcid":"https://orcid.org/0000-0002-4399-0572","affiliations":[{"raw_affiliation_string":"Ear, Nose and Throat Department, Leeds Teaching Hospitals NHS Trust, Leeds, U.K","institution_ids":["https://openalex.org/I2799390153"]},{"raw_affiliation_string":"Ear, Nose and Throat Department Leeds Teaching Hospitals NHS Trust, Leeds, UK","institution_ids":["https://openalex.org/I2799390153"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060810496","display_name":"Luisa Cutillo","orcid":"https://orcid.org/0000-0002-2205-0338"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Luisa Cutillo","raw_affiliation_strings":["Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, U.K","Faculty of Engineering and Physical Sciences University of Leeds, Leeds, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]},{"raw_affiliation_string":"Faculty of Engineering and Physical Sciences University of Leeds, Leeds, UK","institution_ids":["https://openalex.org/I130828816"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7367,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68270254,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"13","issue":null,"first_page":"58465","last_page":"58480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.7764999866485596,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10863","display_name":"Voice and Speech Disorders","score":0.7764999866485596,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10201","display_name":"Speech Recognition and Synthesis","score":0.766700029373169,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7029589414596558},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4703559875488281},{"id":"https://openalex.org/keywords/throat","display_name":"Throat","score":0.4670155644416809},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3997569680213928},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.15175381302833557}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7029589414596558},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4703559875488281},{"id":"https://openalex.org/C2776989088","wikidata":"https://www.wikidata.org/wiki/Q16364","display_name":"Throat","level":2,"score":0.4670155644416809},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3997569680213928},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.15175381302833557},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2025.3555767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3555767","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:224935","is_oa":false,"landing_page_url":"https://orcid.org/0009-0004-9144-0438>,","pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:3639e7d5b5624c94ae1f6f5ef8ebfdf0","is_oa":true,"landing_page_url":"https://doaj.org/article/3639e7d5b5624c94ae1f6f5ef8ebfdf0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 58465-58480 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3555767","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3555767","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.6800000071525574}],"awards":[{"id":"https://openalex.org/G409824404","display_name":"UKRI Centre for Doctoral Training in Artificial Intelligence for Medical Diagnosis and Care","funder_award_id":"EP/S024336/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2018662856","https://openalex.org/W1526391617","https://openalex.org/W2147212203","https://openalex.org/W2463157214","https://openalex.org/W4297679300","https://openalex.org/W2145696447","https://openalex.org/W2357834577"],"abstract_inverted_index":{"Cases":[0],"of":[1,54,99,115,197,255],"throat":[2,30,60,116,240],"cancer":[3,31,61,117,241],"are":[4],"rising":[5],"worldwide.":[6],"With":[7],"survival":[8],"decreasing":[9],"significantly":[10],"at":[11],"later":[12],"stages,":[13],"early":[14],"detection":[15],"is":[16,214],"vital.":[17],"Artificial":[18],"intelligence":[19],"(AI)":[20],"and":[21,38,56,77,101,111,150,156,168,181,206,219,251],"machine":[22],"learning":[23],"(ML)":[24],"have":[25],"the":[26,40,52,113,169,189,253],"potential":[27],"to":[28,67,82],"detect":[29],"from":[32,62,242],"patient":[33],"speech,":[34],"facilitating":[35],"earlier":[36],"diagnosis":[37],"reducing":[39],"burden":[41],"on":[42,126,248],"overstretched":[43],"healthcare":[44],"systems.":[45],"However,":[46],"no":[47,229],"comprehensive":[48],"review":[49,65,93,226],"has":[50],"explored":[51],"use":[53],"AI":[55],"ML":[57,110],"for":[58,216],"detecting":[59,239],"speech.":[63,243],"This":[64],"aims":[66],"fill":[68],"this":[69,223],"gap":[70],"by":[71],"evaluating":[72],"how":[73],"these":[74],"technologies":[75],"perform":[76],"identifying":[78],"issues":[79],"that":[80,106,152,228],"need":[81],"be":[83],"addressed":[84],"in":[85,119,222,238],"future":[86],"research.":[87],"We":[88,103,134,176,184],"conducted":[89],"a":[90,194],"scoping":[91],"literature":[92],"across":[94],"three":[95,208],"databases:":[96],"Scopus,":[97],"Web":[98],"Science,":[100],"PubMed.":[102],"included":[104],"articles":[105,137],"classified":[107],"speech":[108],"using":[109,209],"specified":[112],"inclusion":[114,140],"patients":[118],"their":[120],"data.":[121,211],"Articles":[122],"were":[123],"categorised":[124],"based":[125],"whether":[127],"they":[128],"performed":[129],"binary":[130,144,155],"or":[131,232],"multi-class":[132,148,157],"classification.":[133,158],"found":[135],"27":[136],"fitting":[138],"our":[139],"criteria,":[141],"12":[142],"performing":[143,147],"classification,":[145,149],"13":[146],"two":[151],"do":[153],"both":[154],"The":[159],"most":[160,170],"common":[161],"classification":[162],"method":[163,231],"used":[164],"was":[165,174],"neural":[166],"networks,":[167],"frequently":[171],"extracted":[172],"feature":[173,234],"mel-spectrograms.":[175],"also":[177],"documented":[178],"pre-processing":[179],"methods":[180],"classifier":[182],"performance.":[183],"compared":[185],"each":[186],"article":[187,203],"against":[188],"TRIPOD-AI":[190],"checklist,":[191],"which":[192],"showed":[193],"significant":[195],"lack":[196],"open":[198],"science,":[199],"with":[200],"only":[201,207],"one":[202],"sharing":[204],"code":[205,213],"open-access":[210],"Open-source":[212],"essential":[215],"external":[217],"validation":[218],"further":[220],"development":[221],"field.":[224],"Our":[225],"indicates":[227],"single":[230],"specific":[233],"consistently":[235],"outperforms":[236],"others":[237],"Future":[244],"research":[245],"should":[246],"focus":[247],"standardising":[249],"methodologies":[250],"improving":[252],"reproducibility":[254],"results.":[256]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
