{"id":"https://openalex.org/W3196572107","doi":"https://doi.org/10.1109/access.2021.3107498","title":"A Machine Learning-Aided Framework to Predict Outcomes of Anti-PD-1 Therapy for Patients With Gynecological Cancer on Incomplete Post-Marketing Surveillance Dataset","display_name":"A Machine Learning-Aided Framework to Predict Outcomes of Anti-PD-1 Therapy for Patients With Gynecological Cancer on Incomplete Post-Marketing Surveillance Dataset","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3196572107","doi":"https://doi.org/10.1109/access.2021.3107498","mag":"3196572107"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3107498","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3107498","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09521878.pdf","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://ieeexplore.ieee.org/ielx7/6287639/6514899/09521878.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100373349","display_name":"Xiaomei Liu","orcid":"https://orcid.org/0000-0003-0934-7249"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaomei Liu","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China. (e-mail: lxm992@163.com)","Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China;"],"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China. (e-mail: lxm992@163.com)","institution_ids":["https://openalex.org/I91656880"]},{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China;","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037671044","display_name":"Zhifeng Xiao","orcid":"https://orcid.org/0000-0003-3327-8108"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhifeng Xiao","raw_affiliation_strings":["School of Engineering, Penn State Erie, The Behrend College, Erie, PA 16563, USA"],"affiliations":[{"raw_affiliation_string":"School of Engineering, Penn State Erie, The Behrend College, Erie, PA 16563, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088910755","display_name":"Song Yang","orcid":"https://orcid.org/0000-0001-6046-5756"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Song","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China"],"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101420108","display_name":"Ruizhe Zhang","orcid":"https://orcid.org/0000-0003-0676-0900"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizhe Zhang","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China"],"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101464948","display_name":"Xiuqin Li","orcid":"https://orcid.org/0000-0002-3805-4990"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuqin Li","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China"],"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China","institution_ids":["https://openalex.org/I91656880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101716100","display_name":"Zhenhua Du","orcid":"https://orcid.org/0000-0002-3102-6145"},"institutions":[{"id":"https://openalex.org/I91656880","display_name":"China Medical University","ror":"https://ror.org/032d4f246","country_code":"CN","type":"education","lineage":["https://openalex.org/I91656880"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenhua Du","raw_affiliation_strings":["Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China"],"affiliations":[{"raw_affiliation_string":"Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China","institution_ids":["https://openalex.org/I91656880"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100373349"],"corresponding_institution_ids":["https://openalex.org/I91656880"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0996,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.7738406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"120464","last_page":"120480"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9970999956130981,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9970999956130981,"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/T10158","display_name":"Cancer Immunotherapy and Biomarkers","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"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/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6973235607147217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6929302215576172},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6040524840354919},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5640825033187866},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.5621450543403625},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.4123295545578003},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.3705400824546814},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32882195711135864},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.12027627229690552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6973235607147217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6929302215576172},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6040524840354919},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5640825033187866},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.5621450543403625},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.4123295545578003},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.3705400824546814},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32882195711135864},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.12027627229690552}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3107498","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3107498","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09521878.pdf","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:doaj.org/article:29cbdc83d28d4640a258fa4b89809e78","is_oa":true,"landing_page_url":"https://doaj.org/article/29cbdc83d28d4640a258fa4b89809e78","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 120464-120480 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3107498","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3107498","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09521878.pdf","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":[{"display_name":"Good health and well-being","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/3"}],"awards":[{"id":"https://openalex.org/G7404917057","display_name":null,"funder_award_id":"2020-BS-099","funder_id":"https://openalex.org/F4320327473","funder_display_name":"Department of Science and Technology of Liaoning Province"},{"id":"https://openalex.org/G7653687964","display_name":null,"funder_award_id":"2020.05.01-2023.04.30","funder_id":"https://openalex.org/F4320327473","funder_display_name":"Department of Science and Technology of Liaoning Province"}],"funders":[{"id":"https://openalex.org/F4320327473","display_name":"Department of Science and Technology of Liaoning Province","ror":"https://ror.org/02f09cx53"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3196572107.pdf","grobid_xml":"https://content.openalex.org/works/W3196572107.grobid-xml"},"referenced_works_count":98,"referenced_works":["https://openalex.org/W14214433","https://openalex.org/W179179905","https://openalex.org/W1485955713","https://openalex.org/W1583700199","https://openalex.org/W1808644423","https://openalex.org/W1968969471","https://openalex.org/W1976364950","https://openalex.org/W1977185509","https://openalex.org/W1984514442","https://openalex.org/W2009093141","https://openalex.org/W2056132907","https://openalex.org/W2056168656","https://openalex.org/W2064186732","https://openalex.org/W2088171019","https://openalex.org/W2092829070","https://openalex.org/W2097744101","https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2106393550","https://openalex.org/W2116079122","https://openalex.org/W2119821739","https://openalex.org/W2134843796","https://openalex.org/W2140404878","https://openalex.org/W2148143831","https://openalex.org/W2160834915","https://openalex.org/W2177405394","https://openalex.org/W2216946510","https://openalex.org/W2238461883","https://openalex.org/W2295598076","https://openalex.org/W2513386338","https://openalex.org/W2519517504","https://openalex.org/W2604262106","https://openalex.org/W2609731728","https://openalex.org/W2621909488","https://openalex.org/W2753111111","https://openalex.org/W2765449478","https://openalex.org/W2768348081","https://openalex.org/W2768429453","https://openalex.org/W2783137027","https://openalex.org/W2791496520","https://openalex.org/W2797373921","https://openalex.org/W2803403013","https://openalex.org/W2886393653","https://openalex.org/W2888408613","https://openalex.org/W2895194501","https://openalex.org/W2899728718","https://openalex.org/W2903950532","https://openalex.org/W2907228515","https://openalex.org/W2911964244","https://openalex.org/W2914427235","https://openalex.org/W2917299215","https://openalex.org/W2941454975","https://openalex.org/W2953675148","https://openalex.org/W2962618676","https://openalex.org/W2963258546","https://openalex.org/W2965102627","https://openalex.org/W2966309635","https://openalex.org/W2970602317","https://openalex.org/W2974688611","https://openalex.org/W2978631110","https://openalex.org/W2983030060","https://openalex.org/W2990989869","https://openalex.org/W2995577021","https://openalex.org/W2999096842","https://openalex.org/W3001912486","https://openalex.org/W3018008580","https://openalex.org/W3024048796","https://openalex.org/W3027015150","https://openalex.org/W3043451120","https://openalex.org/W3087661601","https://openalex.org/W3087827179","https://openalex.org/W3091880139","https://openalex.org/W3094948551","https://openalex.org/W3098198535","https://openalex.org/W3102476541","https://openalex.org/W3103134014","https://openalex.org/W3107820270","https://openalex.org/W3109637979","https://openalex.org/W3120076108","https://openalex.org/W3126390605","https://openalex.org/W3138105809","https://openalex.org/W3138886979","https://openalex.org/W3174278992","https://openalex.org/W3183512578","https://openalex.org/W4235051201","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W6600554218","https://openalex.org/W6607259140","https://openalex.org/W6628983204","https://openalex.org/W6674385629","https://openalex.org/W6675354045","https://openalex.org/W6680531176","https://openalex.org/W6744292511","https://openalex.org/W6745609711","https://openalex.org/W6751145664","https://openalex.org/W6788274485","https://openalex.org/W6791728320"],"related_works":["https://openalex.org/W2181530120","https://openalex.org/W4211215373","https://openalex.org/W2024529227","https://openalex.org/W1574575415","https://openalex.org/W3144172081","https://openalex.org/W3028371478","https://openalex.org/W2081476516","https://openalex.org/W2581984549","https://openalex.org/W3179858851","https://openalex.org/W3123177881"],"abstract_inverted_index":{"Post-marketing":[0],"surveillance":[1,81],"of":[2,57,96,153,204,212,229,243],"antineoplastic":[3],"agents":[4],"is":[5,28,46,75,198],"performed":[6],"to":[7,92,164,173],"evaluate":[8],"the":[9,79,94,146,166,181,187,241,244],"efficacy":[10],"and":[11,20,118,138,161,186,214,220,224,232,238],"safety":[12],"in":[13,42,78,128],"patients":[14],"aiming":[15],"at":[16],"expanding":[17],"drug":[18],"indications":[19],"discovering":[21],"potential":[22],"adverse":[23,133],"events.":[24],"The":[25,142,191,235],"real-world":[26],"data":[27,41],"fraught":[29],"with":[30,39,105],"missing":[31,40],"values.":[32],"Literature":[33],"addressing":[34],"different":[35],"strategies":[36,185],"for":[37,53,99,194],"dealing":[38],"such":[43,179],"a":[44,65,89,103,149,201,209,226],"situation":[45],"scarce.":[47],"Using":[48],"machine":[49],"learning":[50,150,196],"(ML)":[51],"algorithms":[52],"predicting":[54],"therapeutic":[55,122],"outcomes":[56,95],"PD-1/PD-L1":[58],"Inhibitors":[59],"has":[60],"attracted":[61],"attention.":[62],"However,":[63],"training":[64],"predictive":[66,168],"model":[67,157,162,193,205,222,230],"usually":[68],"requires":[69],"imaging":[70],"or":[71],"biomarker":[72],"information,":[73],"which":[74],"rarely":[76],"available":[77],"post-marketing":[80],"data.":[82],"To":[83],"address":[84],"these":[85],"challenges,":[86],"we":[87,217],"propose":[88],"ML-aided":[90],"framework":[91,144],"predict":[93],"Anti-PD-1":[97],"therapy":[98],"gynecological":[100],"malignancy":[101],"on":[102,208],"dataset":[104,147],"117":[106],"patient":[107,114],"samples,":[108],"treated":[109],"by":[110],"Camrelizumab":[111],"(with":[112],"50":[113],"samples),":[115],"Sintilimab":[116],"(44),":[117],"Toripalimab":[119],"(23).":[120],"Four":[121],"outcomes,":[123],"including":[124],"Response":[125],"Evaluation":[126],"Criteria":[127],"Solid":[129],"Tumours":[130],"(RECIST),":[131],"organ":[132],"effect":[134],"(AE),":[135],"general":[136],"AE,":[137],"death,":[139],"are":[140],"predicted.":[141],"proposed":[143,245],"feeds":[145],"into":[148],"pipeline":[151],"consisting":[152],"imputation,":[154],"feature":[155,183,233],"engineering,":[156],"training,":[158],"ensemble":[159],"learning,":[160],"selection":[163],"generate":[165],"final":[167,192],"model.":[169],"We":[170],"conduct":[171,218],"experiments":[172],"justify":[174],"several":[175],"critical":[176],"design":[177],"choices,":[178],"as":[180],"specific":[182],"engineering":[184],"SMOTE":[188],"over-sampling":[189],"technique.":[190],"each":[195],"task":[197],"selected":[199],"from":[200],"large":[202],"pool":[203],"candidates":[206],"based":[207],"joint":[210],"consideration":[211],"accuracy":[213],"F1.":[215],"Moreover,":[216],"thorough":[219],"visualized":[221],"analysis":[223],"gain":[225],"deeper":[227],"understanding":[228],"behavior":[231],"importance.":[234],"results,":[236],"analysis,":[237],"findings":[239],"demonstrate":[240],"superiority":[242],"learning-aided":[246],"framework.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}