{"id":"https://openalex.org/W4405427386","doi":"https://doi.org/10.1145/3698587.3701353","title":"Rethinking Radiology Report Generation via Causal Inspired Counterfactual Augmentation","display_name":"Rethinking Radiology Report Generation via Causal Inspired Counterfactual Augmentation","publication_year":2024,"publication_date":"2024-11-22","ids":{"openalex":"https://openalex.org/W4405427386","doi":"https://doi.org/10.1145/3698587.3701353"},"language":"en","primary_location":{"id":"doi:10.1145/3698587.3701353","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698587.3701353","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3698587.3701353","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101526673","display_name":"Xiao Song","orcid":"https://orcid.org/0000-0001-6352-6542"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]},{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Song","raw_affiliation_strings":["Nanjing University, Suzhou, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"Nanjing University, Suzhou, Jiangsu, China","institution_ids":["https://openalex.org/I3923682","https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112949052","display_name":"Jiafan Liu","orcid":"https://orcid.org/0000-0002-9720-2471"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jiafan Liu","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115604885","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0003-3154-5778"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Liu","raw_affiliation_strings":["Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100369231","display_name":"Yun Li","orcid":"https://orcid.org/0000-0003-0935-9274"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210128921","display_name":"The First Affiliated Hospital, Sun Yat-sen University","ror":"https://ror.org/037p24858","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Li","raw_affiliation_strings":["The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210128921","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004296782","display_name":"Wenbin Lei","orcid":"https://orcid.org/0000-0002-9720-1997"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210128921","display_name":"The First Affiliated Hospital, Sun Yat-sen University","ror":"https://ror.org/037p24858","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbin Lei","raw_affiliation_strings":["The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210128921","https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065798206","display_name":"Ruxin Wang","orcid":"https://orcid.org/0000-0003-4772-3284"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruxin Wang","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101526673"],"corresponding_institution_ids":["https://openalex.org/I3923682","https://openalex.org/I881766915"],"apc_list":null,"apc_paid":null,"fwci":0.683,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.7721358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9993000030517578,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.84464430809021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5028957724571228},{"id":"https://openalex.org/keywords/medical-physics","display_name":"Medical physics","score":0.34959107637405396},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.33551090955734253},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.21745356917381287}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.84464430809021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5028957724571228},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.34959107637405396},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.33551090955734253},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.21745356917381287},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698587.3701353","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698587.3701353","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3698587.3701353","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698587.3701353","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5309134341","display_name":null,"funder_award_id":"62102410, 12101334","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1895577753","https://openalex.org/W1905882502","https://openalex.org/W2101105183","https://openalex.org/W2152772232","https://openalex.org/W2486285194","https://openalex.org/W2549599535","https://openalex.org/W2745461083","https://openalex.org/W2770165365","https://openalex.org/W2903721568","https://openalex.org/W2997704374","https://openalex.org/W3035512383","https://openalex.org/W3039671729","https://openalex.org/W3096809860","https://openalex.org/W3098325931","https://openalex.org/W3104609094","https://openalex.org/W3169001897","https://openalex.org/W3204924011","https://openalex.org/W4287727072","https://openalex.org/W4315750691","https://openalex.org/W4386065580","https://openalex.org/W4386075874","https://openalex.org/W4386076127","https://openalex.org/W4388343614","https://openalex.org/W4392450060","https://openalex.org/W4399767250"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3031052312","https://openalex.org/W4389568370","https://openalex.org/W3201448254","https://openalex.org/W3032375762","https://openalex.org/W4286970243","https://openalex.org/W1995515455","https://openalex.org/W2080531066"],"abstract_inverted_index":{"Radiology":[0],"Report":[1,143],"Generation":[2],"(RRG)":[3],"draws":[4],"attention":[5],"as":[6,30,100],"a":[7,82,122,176],"vision-and-language":[8],"interaction":[9],"of":[10,18,41,52,157,171,194],"biomedical":[11],"fields.":[12],"Previous":[13],"works":[14],"inherited":[15],"the":[16,35,45,50,57,75,79,90,96,103,110,115,133,140,148,153,163,169,192,201],"ideology":[17],"traditional":[19],"language":[20],"generation":[21],"tasks,":[22],"aiming":[23],"to":[24,68,146],"generate":[25],"paragraphs":[26],"with":[27],"high":[28],"readability":[29],"reports.":[31,64],"Despite":[32],"significant":[33],"progress,":[34],"independence":[36],"between":[37,78,93],"diseases---a":[38],"specific":[39],"property":[40],"RRG---was":[42],"neglected,":[43],"yielding":[44],"models":[46],"being":[47],"confused":[48],"by":[49,56,197],"co-occurrence":[51,91,195],"diseases":[53,94],"brought":[54],"on":[55,95,162,181,200],"biased":[58,97],"data":[59],"distribution,":[60],"thus":[61,151],"generating":[62],"inaccurate":[63],"In":[65],"this":[66,70],"paper,":[67],"rethink":[69],"issue,":[71],"we":[72,87,120],"first":[73],"model":[74],"causal":[76,83],"effects":[77],"variables":[80],"from":[81],"perspective,":[84],"through":[85,105],"which":[86,185],"prove":[88],"that":[89,128],"relationships":[92],"distribution":[98],"function":[99],"confounders,":[101],"confusing":[102],"accuracy":[104,154],"two":[106,130],"backdoor":[107,149],"paths,":[108,150],"i.e.":[109,132],"Joint":[111],"Vision":[112],"Coupling":[113],"and":[114,139,155],"Conditional":[116],"Sequential":[117],"Coupling.":[118],"Then,":[119],"proposed":[121,173],"novel":[123],"model-agnostic":[124],"counterfactual":[125],"augmentation":[126],"method":[127],"contains":[129],"strategies,":[131],"Prototype-based":[134],"Counterfactual":[135,142],"Sample":[136],"Synthesis":[137],"(P-CSS)":[138],"Magic-Cube-like":[141],"Reconstruction":[144],"(Cube),":[145],"intervene":[147],"enhancing":[152],"generalization":[156,177],"RRG":[158],"models.":[159],"Experimental":[160],"results":[161],"widely":[164],"used":[165],"MIMIC-CXR":[166],"dataset":[167],"demonstrate":[168],"effectiveness":[170],"our":[172,187],"method.":[174],"Additionally,":[175],"performance":[178],"is":[179],"evaluated":[180],"IU":[182],"X-Ray":[183],"dataset,":[184],"verifies":[186],"work":[188],"can":[189],"effectively":[190],"reduce":[191],"impact":[193],"caused":[196],"different":[198],"distributions":[199],"results.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
