{"id":"https://openalex.org/W7165382501","doi":"https://doi.org/10.1016/j.ijmedinf.2026.106549","title":"Current progress and obstacles for automated classification of causes of death based on death certificates: A systematic review","display_name":"Current progress and obstacles for automated classification of causes of death based on death certificates: A systematic review","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165382501","doi":"https://doi.org/10.1016/j.ijmedinf.2026.106549","pmid":"https://pubmed.ncbi.nlm.nih.gov/42320083"},"language":"en","primary_location":{"id":"doi:10.1016/j.ijmedinf.2026.106549","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijmedinf.2026.106549","pdf_url":null,"source":{"id":"https://openalex.org/S53142634","display_name":"International Journal of Medical Informatics","issn_l":"1386-5056","issn":["1386-5056","1872-8243"],"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":"International Journal of Medical Informatics","raw_type":"journal-article"},"type":"review","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.ijmedinf.2026.106549","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5079741382","display_name":"Chaiquan Li","orcid":"https://orcid.org/0000-0002-4391-6823"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Chaiquan Li","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123495685","display_name":"QINGYU MENG","orcid":null},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Qingyu Meng","raw_affiliation_strings":["Department of Statistics, University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033839978","display_name":"Sue Wells","orcid":"https://orcid.org/0000-0003-2942-9524"},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Sue Wells","raw_affiliation_strings":["Department of General Practice, University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of General Practice, University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033997225","display_name":"Sebastiano Barbieri","orcid":"https://orcid.org/0000-0002-5919-372X"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Sebastiano Barbieri","raw_affiliation_strings":["Queensland Digital Health Centre, The University of Queensland, Brisbane, Australia; Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queensland Digital Health Centre, The University of Queensland, Brisbane, Australia; Centre for Big Data Research in Health, University of New South Wales, Sydney, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122271360","display_name":"Rod Jackson","orcid":null},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Rod Jackson","raw_affiliation_strings":["Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Epidemiology and Biostatistics, University of Auckland, Auckland, New Zealand","institution_ids":["https://openalex.org/I154130895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5138977885","display_name":"Katrina Poppe","orcid":null},"institutions":[{"id":"https://openalex.org/I154130895","display_name":"University of Auckland","ror":"https://ror.org/03b94tp07","country_code":"NZ","type":"education","lineage":["https://openalex.org/I154130895"]},{"id":"https://openalex.org/I39854758","display_name":"Auckland University of Technology","ror":"https://ror.org/01zvqw119","country_code":"NZ","type":"education","lineage":["https://openalex.org/I39854758"]}],"countries":["NZ"],"is_corresponding":true,"raw_author_name":"Katrina Poppe","raw_affiliation_strings":["Department of Medicine, University of Auckland, Auckland, New Zealand. Electronic address: k.poppe@auckland.ac.nz"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medicine, University of Auckland, Auckland, New Zealand. Electronic address: k.poppe@auckland.ac.nz","institution_ids":["https://openalex.org/I154130895","https://openalex.org/I39854758"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5138977885"],"corresponding_institution_ids":["https://openalex.org/I154130895","https://openalex.org/I39854758"],"apc_list":{"value":3210,"currency":"USD","value_usd":3210},"apc_paid":{"value":3210,"currency":"USD","value_usd":3210},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71759891,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"219","issue":null,"first_page":"106549","last_page":"106549"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12296","display_name":"Autopsy Techniques and Outcomes","score":0.5638999938964844,"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/T12296","display_name":"Autopsy Techniques and Outcomes","score":0.5638999938964844,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.08070000261068344,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.03500000014901161,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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/coding","display_name":"Coding (social sciences)","score":0.49459999799728394},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4440999925136566},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.43860000371932983},{"id":"https://openalex.org/keywords/cause-of-death","display_name":"Cause of death","score":0.3953000009059906},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3732999861240387},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.3230000138282776},{"id":"https://openalex.org/keywords/scopus","display_name":"Scopus","score":0.31470000743865967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251000165939331},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.566100001335144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5623999834060669},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.49459999799728394},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.43860000371932983},{"id":"https://openalex.org/C29374701","wikidata":"https://www.wikidata.org/wiki/Q1931388","display_name":"Cause of death","level":3,"score":0.3953000009059906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3732999861240387},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.3230000138282776},{"id":"https://openalex.org/C83867959","wikidata":"https://www.wikidata.org/wiki/Q371467","display_name":"Scopus","level":3,"score":0.31470000743865967},{"id":"https://openalex.org/C2776650193","wikidata":"https://www.wikidata.org/wiki/Q264661","display_name":"Obstacle","level":2,"score":0.3122999966144562},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.30660000443458557},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3012000024318695},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2953999936580658},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.27639999985694885},{"id":"https://openalex.org/C145642194","wikidata":"https://www.wikidata.org/wiki/Q870895","display_name":"Health informatics","level":3,"score":0.2727000117301941},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2669000029563904},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.ijmedinf.2026.106549","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijmedinf.2026.106549","pdf_url":null,"source":{"id":"https://openalex.org/S53142634","display_name":"International Journal of Medical Informatics","issn_l":"1386-5056","issn":["1386-5056","1872-8243"],"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":"International Journal of Medical Informatics","raw_type":"journal-article"},{"id":"pmid:42320083","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42320083","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":"International journal of medical informatics","raw_type":null}],"best_oa_location":{"id":"doi:10.1016/j.ijmedinf.2026.106549","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ijmedinf.2026.106549","pdf_url":null,"source":{"id":"https://openalex.org/S53142634","display_name":"International Journal of Medical Informatics","issn_l":"1386-5056","issn":["1386-5056","1872-8243"],"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":"International Journal of Medical Informatics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.5323904752731323,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320780","display_name":"National Heart Foundation of New Zealand","ror":"https://ror.org/02xwkbq98"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320334749","display_name":"Health Research Council of New Zealand","ror":"https://ror.org/00zbf3d93"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1760646631","https://openalex.org/W2076749608","https://openalex.org/W2107638293","https://openalex.org/W2315364169","https://openalex.org/W2563349699","https://openalex.org/W2732690754","https://openalex.org/W2789326915","https://openalex.org/W2800235673","https://openalex.org/W2801547136","https://openalex.org/W2885195348","https://openalex.org/W2888293940","https://openalex.org/W2888359010","https://openalex.org/W2903133697","https://openalex.org/W2944571303","https://openalex.org/W2946575095","https://openalex.org/W2947667755","https://openalex.org/W2954102128","https://openalex.org/W2976274315","https://openalex.org/W2988001370","https://openalex.org/W2995940367","https://openalex.org/W3007800087","https://openalex.org/W3018601113","https://openalex.org/W3038294580","https://openalex.org/W3117651508","https://openalex.org/W3118615836","https://openalex.org/W3138184602","https://openalex.org/W3193700584","https://openalex.org/W3205844213","https://openalex.org/W3217177838","https://openalex.org/W4206681774","https://openalex.org/W4212809570","https://openalex.org/W4223926712","https://openalex.org/W4226200347","https://openalex.org/W4288080910","https://openalex.org/W4307138871","https://openalex.org/W4307217099","https://openalex.org/W4388199535","https://openalex.org/W4395673502","https://openalex.org/W4398771763"],"related_works":[],"abstract_inverted_index":{"OBJECTIVE:":[0],"While":[1],"manual":[2],"coding":[3,45],"or":[4,46,87],"rule-based":[5,182,272,284],"software":[6],"are":[7,299],"approaches":[8,162,298],"used":[9,82,136,163],"by":[10,102,301],"most":[11,160],"countries":[12],"for":[13,49,65,126,221,242,252,261],"cause":[14,50],"of":[15,20,33,43,51,91,116,133,141,170,229,237,256,264,269,292,304],"death":[16,52,265],"classification,":[17,53],"the":[18,29,40,55,61,89,97,109,117,139,145,149,191,225,232,302,305],"application":[19],"advanced":[21],"deep":[22,165,243,257,278],"learning":[23,166,244,258,279],"tools":[24,48,84,118,273],"is":[25,288,295],"likely":[26],"to":[27,76,78,85,137,156,199,209,235],"enhance":[28],"efficiency":[30],"and":[31,60,63,69,114,123,177,181,201,217,248,266,290],"accuracy":[32],"national":[34],"mortality":[35],"statistics.":[36],"To":[37],"systematically":[38,72],"review":[39],"current":[41],"implementation":[42,127,236],"automated":[44,83,239],"categorising":[47],"summarising":[54],"methodologies":[56],"applied,":[57],"performance":[58,115,255,270,287],"achieved,":[59],"progress":[62,122],"obstacles":[64,125],"application.":[66],"METHODS:":[67],"PubMed":[68],"Scopus":[70],"were":[71,119,164,173,179,250,274],"searched":[73],"from":[74,154,197,207],"2018":[75],"2024":[77],"identify":[79],"studies":[80],"that":[81],"code":[86],"categorise":[88],"causes":[90,263],"death.":[92],"Two":[93],"researchers":[94],"independently":[95],"selected":[96],"papers":[98],"with":[99,121,193,271],"disagreement":[100],"adjudicated":[101],"a":[103],"third":[104],"supervisor.":[105],"For":[106],"each":[107],"study,":[108],"general":[110],"profile,":[111],"detailed":[112],"methodology,":[113],"extracted":[120],"potential":[124],"assessed":[128],"qualitatively.":[129],"An":[130],"adapted":[131],"version":[132],"QUADAS-2":[134],"was":[135,212,231,259],"assess":[138],"risk":[140],"bias.":[142],"RESULTS:":[143],"Among":[144],"46":[146],"included":[147],"studies,":[148],"training":[150,306],"sample":[151],"size":[152],"ranged":[153],"165":[155],"10,519,268":[157],"people.":[158],"The":[159,254],"popular":[161],"(n":[167,183],"=":[168,184],"22,":[169],"which":[171],"7":[172],"recurrent":[174],"neural":[175],"network":[176],"6":[178],"transformer)":[180],"15)":[185],"automation.":[186],"Large":[187],"disparities":[188],"existed":[189],"in":[190],"performance,":[192],"recall":[194,216],"(sensitivity)":[195],"ranging":[196,206],"0.253":[198],"1.000":[200],"precision":[202],"(positive":[203],"predictive":[204],"value)":[205],"0.396":[208],"1.000.":[210],"Precision":[211],"often":[213],"higher":[214],"than":[215],"could":[218],"vary":[219],"substantially":[220],"different":[222],"settings":[223],"within":[224],"same":[226],"study.":[227],"Quality":[228],"text":[230],"major":[233],"obstacle":[234],"older":[238],"tools,":[240,285],"while":[241],"models,":[245],"target":[246],"task":[247],"materials":[249],"required":[251],"pre-training.":[253],"unsatisfactory":[260],"infrequent":[262],"head-to-head":[267,293],"comparisons":[268,294],"limited.":[275],"CONCLUSION:":[276],"Despite":[277],"applications":[280],"gaining":[281],"popularity":[282],"over":[283],"their":[286],"inconsistent":[289],"evidence":[291],"insufficient.":[296],"All":[297],"influenced":[300],"quality":[303],"data.":[307]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-06-20T00:00:00"}