{"id":"https://openalex.org/W4407789787","doi":"https://doi.org/10.3233/idt-230504","title":"Construction of the statistical prediction model for the probability of liver cancer based on interpretable artificial intelligence logic","display_name":"Construction of the statistical prediction model for the probability of liver cancer based on interpretable artificial intelligence logic","publication_year":2024,"publication_date":"2024-11-01","ids":{"openalex":"https://openalex.org/W4407789787","doi":"https://doi.org/10.3233/idt-230504"},"language":"en","primary_location":{"id":"doi:10.3233/idt-230504","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230504","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039664493","display_name":"Zhongxing Wang","orcid":"https://orcid.org/0000-0003-3620-5529"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongxing Wang","raw_affiliation_strings":["College of Science and Technology, Shenyang Polytechnic College, Shenyang, China","E-mail:"],"affiliations":[{"raw_affiliation_string":"College of Science and Technology, Shenyang Polytechnic College, Shenyang, China","institution_ids":["https://openalex.org/I157507598"]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5039664493"],"corresponding_institution_ids":["https://openalex.org/I157507598"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.38248454,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"4","first_page":"2961","last_page":"2975"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9458000063896179,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.9458000063896179,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9358999729156494,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.5714770555496216},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5281980633735657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.432406485080719}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5714770555496216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5281980633735657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.432406485080719}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-230504","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-230504","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W3190033465","https://openalex.org/W3195827568","https://openalex.org/W4205165875","https://openalex.org/W4206171405","https://openalex.org/W4206479908","https://openalex.org/W4206769964","https://openalex.org/W4210368835","https://openalex.org/W4220909506","https://openalex.org/W4223992509","https://openalex.org/W4224278548","https://openalex.org/W4280535237","https://openalex.org/W4283759983","https://openalex.org/W4285116075","https://openalex.org/W4286220017","https://openalex.org/W4293173433","https://openalex.org/W4296838339","https://openalex.org/W4297339085","https://openalex.org/W4312130564"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W3046775127","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474"],"abstract_inverted_index":{"Current":[0],"machine":[1,32],"learning":[2],"models":[3,46],"under":[4,47,83],"artificial":[5],"intelligence":[6],"can":[7],"only":[8],"improve":[9],"prediction":[10,22,58,168],"accuracy,":[11],"but":[12],"their":[13],"underlying":[14],"logic":[15],"remains":[16],"incomprehensible.":[17],"Therefore,":[18],"to":[19,149],"provide":[20],"high":[21],"accuracy":[23],"and":[24,50,65,68,131,170],"enhance":[25],"the":[26,29,34,37,77,88,97,105,166,176],"interpretability":[27,69],"of":[28,104],"model":[30,42,59],"through":[31,62],"learning,":[33],"study":[35],"selects":[36],"Extreme":[38],"Gradient":[39],"Boosting":[40],"(XGBoost)":[41],"by":[43],"comparing":[44],"multiple":[45],"single":[48,89],"learner":[49,90],"integrated":[51],"learning.":[52],"Then":[53],"a":[54,118,143,151],"cancer":[55,179],"probability":[56],"statistical":[57],"is":[60,146,155,173],"constructed":[61],"parameter":[63],"optimization,":[64],"its":[66,159],"performance":[67],"are":[70],"analyzed.":[71],"The":[72],"experimental":[73],"results":[74],"showed":[75],"that":[76,103],"Receiver":[78],"Operating":[79],"Characteristic":[80],"(ROC)":[81],"Area":[82],"Curve":[84],"(AUC)":[85],"value":[86,99,113,145],"in":[87,111,156],"was":[91,100],"generally":[92],"lower":[93],"than":[94,115],"80%,":[95],"while":[96],"AUC":[98],"84.4%,":[101],"surpassing":[102],"comparison":[106],"model.":[107],"Simultaneously,":[108],"an":[109],"increase":[110],"Alpha-Fetoprotein":[112,132],"greater":[114],"13.5":[116],"had":[117],"stronger":[119],"predictive":[120],"effect":[121],"when":[122],"combined":[123],"with":[124,158],"other":[125],"factors.":[126],"Smaller":[127],"serum":[128],"Alanine":[129],"Aminotransferase":[130],"assay":[133],"near":[134],"0":[135],"may":[136],"produce":[137,150],"negative":[138],"or":[139],"positive":[140,152],"effects,":[141],"whereas":[142],"higher":[144],"more":[147],"likely":[148],"effect.":[153],"This":[154],"line":[157],"clinical":[160],"significance.":[161],"Overall,":[162],"XGBoost":[163],"effectively":[164],"improves":[165],"out-of-sample":[167],"accurate":[169],"interpretability,":[171],"which":[172],"significant":[174],"for":[175],"actual":[177],"liver":[178],"diagnosis":[180],"prediction.":[181]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}