{"id":"https://openalex.org/W4406271405","doi":"https://doi.org/10.1109/bibm62325.2024.10822532","title":"FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes","display_name":"FODA-PG for Enhanced Medical Imaging Narrative Generation: Adaptive Differentiation of Normal and Abnormal Attributes","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406271405","doi":"https://doi.org/10.1109/bibm62325.2024.10822532"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-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/A5101799706","display_name":"Kai Shu","orcid":"https://orcid.org/0000-0002-7275-7315"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kai Shu","raw_affiliation_strings":["University Of Southern California,Viterbi School,Los Angeles,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University Of Southern California,Viterbi School,Los Angeles,United States","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuzhuo Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuzhuo Jia","raw_affiliation_strings":["The University of Sydney,School of Computer Science,Sydney,Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Sydney,School of Computer Science,Sydney,Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100357832","display_name":"Ziyang Zhang","orcid":"https://orcid.org/0000-0002-6229-6877"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyang Zhang","raw_affiliation_strings":["North China University of Techonology,Brunel London School,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North China University of Techonology,Brunel London School,Beijing,China","institution_ids":["https://openalex.org/I1456306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012051562","display_name":"Jiechao Gao","orcid":"https://orcid.org/0000-0003-0628-1416"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiechao Gao","raw_affiliation_strings":["University of Virginia,Department of Computer Science,Charlottesville,United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Virginia,Department of Computer Science,Charlottesville,United States","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101799706"],"corresponding_institution_ids":["https://openalex.org/I1174212"],"apc_list":null,"apc_paid":null,"fwci":2.8681,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93637612,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4564","last_page":"4571"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.40230000019073486,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.40230000019073486,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/narrative","display_name":"Narrative","score":0.6053053736686707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5732190608978271},{"id":"https://openalex.org/keywords/literature","display_name":"Literature","score":0.1483306884765625},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.11375164985656738}],"concepts":[{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.6053053736686707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5732190608978271},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.1483306884765625},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.11375164985656738}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822532","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1956340063","https://openalex.org/W2101105183","https://openalex.org/W2152772232","https://openalex.org/W2745461083","https://openalex.org/W2770165365","https://openalex.org/W2911489562","https://openalex.org/W2962810718","https://openalex.org/W2964051877","https://openalex.org/W2979861699","https://openalex.org/W2995225687","https://openalex.org/W3104609094","https://openalex.org/W3173688449","https://openalex.org/W3181252431","https://openalex.org/W4312762144","https://openalex.org/W4312784228","https://openalex.org/W4382240685","https://openalex.org/W4386076127","https://openalex.org/W4405669265","https://openalex.org/W6637178625","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6726873649","https://openalex.org/W6754929296","https://openalex.org/W6760721734","https://openalex.org/W6768851824","https://openalex.org/W6775843921","https://openalex.org/W6787094702","https://openalex.org/W6789753369","https://openalex.org/W6852542133","https://openalex.org/W6855122778"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2348886128","https://openalex.org/W2388067091","https://openalex.org/W2367656648","https://openalex.org/W2390279801","https://openalex.org/W2350200549","https://openalex.org/W2362132076","https://openalex.org/W2965396777"],"abstract_inverted_index":{"Automatic":[0],"Medical":[1],"Imaging":[2],"Narrative":[3],"generation":[4],"aims":[5],"to":[6,36,54,110],"alleviate":[7],"the":[8,22,45,112,121,159,165,174],"workload":[9],"of":[10,84,123,167,176],"radiologists":[11],"by":[12,87],"producing":[13],"accurate":[14],"clinical":[15,100],"descriptions":[16],"directly":[17],"from":[18],"radiological":[19,85],"images.":[20],"However,":[21],"subtle":[23],"visual":[24],"nuances":[25],"and":[26,50,94,102,117,137,148,161],"domain-specific":[27],"terminology":[28],"in":[29,179],"medical":[30,180],"images":[31],"pose":[32],"significant":[33],"challenges":[34],"compared":[35],"generic":[37],"image":[38],"captioning":[39],"tasks.":[40],"Existing":[41],"approaches":[42],"often":[43],"neglect":[44],"vital":[46],"distinction":[47],"between":[48,115],"normal":[49,116],"abnormal":[51],"findings,":[52],"leading":[53],"suboptimal":[55],"performance.":[56],"In":[57],"this":[58,128],"work,":[59],"we":[60],"propose":[61],"FODA-PG,":[62],"a":[63,80,133],"novel":[64],"Fine-grained":[65],"Organ-Disease":[66],"Adaptive":[67],"Partitioning":[68],"Graph":[69],"framework":[70],"that":[71],"addresses":[72],"these":[73],"limitations":[74],"through":[75],"domain-adaptive":[76],"learning.":[77],"FODA-PG":[78,145],"constructs":[79],"granular":[81],"graphical":[82],"representation":[83],"findings":[86],"separating":[88],"disease-related":[89],"attributes":[90],"into":[91,132],"distinct":[92],"\"disease-specific\"":[93],"\"disease-free\"":[95],"categories":[96],"based":[97],"on":[98,158],"their":[99],"significance":[101],"location.":[103],"This":[104],"adaptive":[105],"partitioning":[106],"enables":[107],"our":[108,168],"model":[109],"capture":[111],"nuanced":[113],"differences":[114],"pathological":[118],"states,":[119],"mitigating":[120],"impact":[122],"data":[124],"biases.":[125],"By":[126],"integrating":[127],"fine-grained":[129],"semantic":[130],"knowledge":[131],"powerful":[134],"transformer-based":[135],"architecture":[136],"providing":[138],"rigorous":[139],"mathematical":[140],"justifications":[141],"for":[142],"its":[143],"effectiveness,":[144],"generates":[146],"precise":[147],"clinically":[149],"coherent":[150],"reports":[151],"with":[152],"enhanced":[153],"generalization":[154],"capabilities.":[155],"Extensive":[156],"experiments":[157],"IU-Xray":[160],"MIMIC-CXR":[162],"benchmarks":[163],"demonstrate":[164],"superiority":[166],"approach":[169],"over":[170],"state-of-the-art":[171],"methods,":[172],"highlighting":[173],"importance":[175],"domain":[177],"adaptation":[178],"report":[181],"generation.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-16T08:24:45.110214","created_date":"2025-10-10T00:00:00"}