{"id":"https://openalex.org/W4416811082","doi":"https://doi.org/10.1007/s44163-025-00685-z","title":"A comprehensive review of the methods of intelligent diagnosis and prediction of COVID-19 disease using machine learning and deep learning techniques","display_name":"A comprehensive review of the methods of intelligent diagnosis and prediction of COVID-19 disease using machine learning and deep learning techniques","publication_year":2025,"publication_date":"2025-11-29","ids":{"openalex":"https://openalex.org/W4416811082","doi":"https://doi.org/10.1007/s44163-025-00685-z"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00685-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00685-z","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1007/s44163-025-00685-z","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5119470256","display_name":"Rasoul Farahi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101274","display_name":"Islamic Azad University of Mahabad","ror":"https://ror.org/015sncd69","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I4210101274"]}],"countries":["IR"],"is_corresponding":true,"raw_author_name":"Rasoul Farahi","raw_affiliation_strings":["Department of Computer Engineering, Mahabad Branch, Islamic Azad University, Mahabad, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, Mahabad Branch, Islamic Azad University, Mahabad, Iran","institution_ids":["https://openalex.org/I4210101274"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089530485","display_name":"M. Pakzad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210101274","display_name":"Islamic Azad University of Mahabad","ror":"https://ror.org/015sncd69","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I4210101274"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Mehri Pakzad","raw_affiliation_strings":["Faculty of Humanities and Basic Sciences, Mahabad Branch, Islamic Azad University, Mahabad, Iran"],"affiliations":[{"raw_affiliation_string":"Faculty of Humanities and Basic Sciences, Mahabad Branch, Islamic Azad University, Mahabad, Iran","institution_ids":["https://openalex.org/I4210101274"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5119470256"],"corresponding_institution_ids":["https://openalex.org/I4210101274"],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.53295669,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"5","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8819000124931335,"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"}},"topics":[{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8819000124931335,"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"}},{"id":"https://openalex.org/T13038","display_name":"Internet of Things and AI","score":0.007199999876320362,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.00430000014603138,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7382000088691711},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.43639999628067017},{"id":"https://openalex.org/keywords/realm","display_name":"Realm","score":0.39489999413490295},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.392300009727478},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.35920000076293945},{"id":"https://openalex.org/keywords/implementation","display_name":"Implementation","score":0.33730000257492065}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8119000196456909},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7613000273704529},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7382000088691711},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5659000277519226},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.44920000433921814},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C2778757428","wikidata":"https://www.wikidata.org/wiki/Q1250464","display_name":"Realm","level":2,"score":0.39489999413490295},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3634999990463257},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.35920000076293945},{"id":"https://openalex.org/C26713055","wikidata":"https://www.wikidata.org/wiki/Q245962","display_name":"Implementation","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.33500000834465027},{"id":"https://openalex.org/C89623803","wikidata":"https://www.wikidata.org/wiki/Q12184","display_name":"Pandemic","level":5,"score":0.29679998755455017},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2847000062465668},{"id":"https://openalex.org/C534262118","wikidata":"https://www.wikidata.org/wiki/Q177719","display_name":"Medical diagnosis","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2624000012874603}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00685-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00685-z","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1e8ab7685939488c9f2cd657bb69adbb","is_oa":true,"landing_page_url":"https://doaj.org/article/1e8ab7685939488c9f2cd657bb69adbb","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-33 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00685-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00685-z","pdf_url":null,"source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W2010347842","https://openalex.org/W2030943647","https://openalex.org/W2893355948","https://openalex.org/W2899439071","https://openalex.org/W3011414569","https://openalex.org/W3013507463","https://openalex.org/W3014725478","https://openalex.org/W3017243633","https://openalex.org/W3017403618","https://openalex.org/W3017644243","https://openalex.org/W3019980738","https://openalex.org/W3022163878","https://openalex.org/W3025948831","https://openalex.org/W3027682070","https://openalex.org/W3027763298","https://openalex.org/W3028070348","https://openalex.org/W3030621456","https://openalex.org/W3038821093","https://openalex.org/W3039563973","https://openalex.org/W3040660552","https://openalex.org/W3042239862","https://openalex.org/W3044240928","https://openalex.org/W3048749423","https://openalex.org/W3049505831","https://openalex.org/W3080568059","https://openalex.org/W3083753334","https://openalex.org/W3089460656","https://openalex.org/W3091270233","https://openalex.org/W3092530991","https://openalex.org/W3109059087","https://openalex.org/W3114083731","https://openalex.org/W3116187740","https://openalex.org/W3117143833","https://openalex.org/W3118490356","https://openalex.org/W3120595226","https://openalex.org/W3120916715","https://openalex.org/W3130844452","https://openalex.org/W3133191822","https://openalex.org/W3135243128","https://openalex.org/W3144777302","https://openalex.org/W3156436924","https://openalex.org/W3157302753","https://openalex.org/W3160132771","https://openalex.org/W3160835377","https://openalex.org/W3161718150","https://openalex.org/W3164988417","https://openalex.org/W3165261737","https://openalex.org/W3166654090","https://openalex.org/W3168955085","https://openalex.org/W3169886559","https://openalex.org/W3174805961","https://openalex.org/W3181644688","https://openalex.org/W3194778829","https://openalex.org/W3195038879","https://openalex.org/W3202092484","https://openalex.org/W3202799525","https://openalex.org/W3214819724","https://openalex.org/W4288699666","https://openalex.org/W4296311345","https://openalex.org/W4297360395","https://openalex.org/W4307298424","https://openalex.org/W4313857678","https://openalex.org/W4318570691","https://openalex.org/W4360976770","https://openalex.org/W4389194971","https://openalex.org/W4390397628","https://openalex.org/W4390579686","https://openalex.org/W4401608335"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"The":[1,166],"disease":[2],"known":[3],"as":[4,84,138,232,234],"COVID-19,":[5,128],"which":[6],"arises":[7],"from":[8,203],"the":[9,37,71,76,85,93,96,113,149,177,190,194,208,215,267,281,297,307,326],"complex":[10],"and":[11,36,61,78,143,162,183,196,237,302],"diverse":[12],"family":[13],"of":[14,30,47,65,81,99,115,123,151,169,192,198,210,217,270,284,299,329],"coronaviruses,":[15],"has":[16,24],"significantly":[17],"progressed":[18],"into":[19,306],"a":[20,28,44,62,121,130,276,313,321],"global":[21],"pandemic":[22],"that":[23,186,207,258],"been":[25,261],"associated":[26],"with":[27,95,129,227],"multitude":[29],"adverse":[31],"consequences":[32],"affecting":[33],"both":[34],"individuals":[35],"broader":[38],"societal":[39],"fabric.":[40],"These":[41],"repercussions":[42],"encompass":[43],"wide":[45],"array":[46],"detrimental":[48],"effects":[49],"on":[50,133,180],"immune":[51],"health,":[52],"overall":[53,327],"well-being,":[54],"substantial":[55],"economic":[56],"downturns,":[57],"rising":[58],"unemployment":[59],"rates,":[60],"stark":[63],"inadequacy":[64],"medical":[66,317],"resources":[67],"available":[68],"to":[69,174,274,288,293],"combat":[70],"crisis.":[72],"In":[73,112,295],"this":[74,116,170,242],"context,":[75],"timely":[77],"accurate":[79],"diagnosis":[80,219],"COVID-19":[82,218],"emerges":[83],"single":[86],"most":[87],"vital":[88],"strategy":[89],"for":[90,127,189],"effectively":[91],"managing":[92,333],"disease,":[94],"overarching":[97],"goal":[98],"reducing":[100],"mortality":[101],"rates":[102],"while":[103,146],"simultaneously":[104],"curbing":[105],"its":[106],"rampant":[107],"transmission":[108],"across":[109],"various":[110,204],"communities.":[111],"pursuit":[114],"objective,":[117],"researchers":[118],"have":[119,259],"explored":[120],"variety":[122],"diagnostic":[124,239,271,308],"methodologies":[125,305],"tailored":[126],"predominant":[131],"reliance":[132],"advanced":[134],"imaging":[135],"techniques":[136],"such":[137,249],"computed":[139],"tomography":[140],"(CT)":[141],"scans":[142],"chest":[144],"X-rays,":[145],"also":[147,320],"emphasizing":[148],"application":[150],"innovative":[152],"data":[153,229],"mining":[154,230],"approaches,":[155],"particularly":[156,290],"those":[157],"rooted":[158],"in":[159,214,244,263,279,291,316,332],"machine":[160,181,300],"learning":[161,164,182,185,212,251,301,304],"deep":[163,184,211,250,303],"paradigms.":[165],"primary":[167],"focus":[168],"scholarly":[171],"paper":[172],"is":[173],"meticulously":[175],"investigate":[176],"strategies":[178],"based":[179],"are":[187,253],"employed":[188],"purpose":[191],"forecasting":[193],"trajectory":[195],"impact":[197],"COVID-19.":[199,294],"Empirical":[200],"findings":[201],"derived":[202],"studies":[205],"indicate":[206],"implementations":[209],"technologies":[213,272],"realm":[216],"generally":[220],"yield":[221],"faster":[222],"approximate":[223],"solutions":[224],"when":[225,248],"juxtaposed":[226],"conventional":[228],"algorithms,":[231],"well":[233],"more":[235],"traditional":[236],"established":[238],"techniques.":[240],"Consequently,":[241],"results":[243],"markedly":[245],"superior":[246],"outcomes":[247],"methods":[252],"compared":[254],"against":[255],"deterministic":[256],"algorithms":[257],"historically":[260],"utilized":[262],"similar":[264],"contexts.":[265],"Thus,":[266],"ongoing":[268],"evolution":[269],"continues":[273],"play":[275],"pivotal":[277],"role":[278],"shaping":[280],"future":[282],"landscape":[283],"public":[285],"health":[286],"responses":[287],"pandemics,":[289],"relation":[292],"conclusion,":[296],"integration":[298],"processes":[309],"represents":[310],"not":[311],"only":[312],"significant":[314],"advancement":[315],"technology":[318],"but":[319],"critical":[322],"step":[323],"towards":[324],"improving":[325],"efficacy":[328],"healthcare":[330],"systems":[331],"infectious":[334],"diseases.":[335]},"counts_by_year":[],"updated_date":"2026-03-17T17:19:04.345684","created_date":"2025-11-29T00:00:00"}