{"id":"https://openalex.org/W4401750760","doi":"https://doi.org/10.1109/isbi56570.2024.10635421","title":"MAKEN: Improving Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models","display_name":"MAKEN: Improving Medical Report Generation with Adapter Tuning and Knowledge Enhancement in Vision-Language Foundation Models","publication_year":2024,"publication_date":"2024-05-27","ids":{"openalex":"https://openalex.org/W4401750760","doi":"https://doi.org/10.1109/isbi56570.2024.10635421"},"language":"en","primary_location":{"id":"doi:10.1109/isbi56570.2024.10635421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5054520274","display_name":"Shibin Wu","orcid":"https://orcid.org/0000-0003-2337-6660"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibin Wu","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101184146","display_name":"Bang Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bang Yang","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029905233","display_name":"Zhiyu Ye","orcid":"https://orcid.org/0009-0001-1520-0051"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyu Ye","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028229824","display_name":"Haoqian Wang","orcid":"https://orcid.org/0000-0003-2792-8469"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqian Wang","raw_affiliation_strings":["Tsinghua University,Shenzhen International Graduate School,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,Shenzhen International Graduate School,Shenzhen,China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102197680","display_name":"Hairong Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hairong Zheng","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100602481","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-8838-4963"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tong Zhang","raw_affiliation_strings":["Peng Cheng Laboratory,Shenzhen,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory,Shenzhen,China","institution_ids":["https://openalex.org/I4210136793"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":11.4746,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.98281685,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9986000061035156,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9932000041007996,"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/adapter","display_name":"Adapter (computing)","score":0.8055769205093384},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.7341126203536987},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6703900098800659},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43894559144973755},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3205113410949707},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.10741230845451355}],"concepts":[{"id":"https://openalex.org/C177284502","wikidata":"https://www.wikidata.org/wiki/Q1005390","display_name":"Adapter (computing)","level":2,"score":0.8055769205093384},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.7341126203536987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6703900098800659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43894559144973755},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3205113410949707},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.10741230845451355},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isbi56570.2024.10635421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi56570.2024.10635421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2159583324","https://openalex.org/W3168867926","https://openalex.org/W3174770825","https://openalex.org/W4229005866","https://openalex.org/W4315628888","https://openalex.org/W4318718936","https://openalex.org/W4323066559","https://openalex.org/W4386234463","https://openalex.org/W4387225791","https://openalex.org/W6791353385","https://openalex.org/W6796581206","https://openalex.org/W6811340617","https://openalex.org/W6849177959","https://openalex.org/W6849374472","https://openalex.org/W6849617328","https://openalex.org/W7064806391"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2133028525","https://openalex.org/W4229060448","https://openalex.org/W4306381730","https://openalex.org/W2981692913","https://openalex.org/W3044188621","https://openalex.org/W3184035966","https://openalex.org/W2485605994","https://openalex.org/W2160602540"],"abstract_inverted_index":{"Medical":[0],"report":[1],"generation":[2],"demands":[3],"automatic":[4],"creation":[5],"of":[6,17,31,35,81,114],"coherent":[7],"and":[8,51,64,75,100,128],"precise":[9],"descriptions":[10],"for":[11,109],"medical":[12,19,66],"images.":[13],"However,":[14],"the":[15,33,47,79,89,110,115],"scarcity":[16],"labelled":[18],"image-report":[20],"pairs":[21],"poses":[22],"formidable":[23],"challenges":[24,121],"in":[25,98,119],"developing":[26],"large-scale":[27,58],"neural":[28],"networks":[29],"capable":[30],"harnessing":[32],"potential":[34],"artificial":[36],"intelligence,":[37],"exemplified":[38],"by":[39,123],"large":[40],"language":[41],"models.":[42,60],"This":[43],"study":[44],"builds":[45],"upon":[46],"state-of-the-art":[48,94],"vision-language":[49,116],"pre-training":[50],"fine-tuning":[52],"approach,":[53],"BLIP-2,":[54],"to":[55],"customize":[56],"general":[57],"foundation":[59,117],"Integrating":[61],"adapter":[62],"tuning":[63],"a":[65],"knowledge":[67],"enhancement":[68],"loss,":[69],"our":[70,85,103],"model":[71,129],"significantly":[72],"improves":[73],"accuracy":[74],"coherence.":[76],"Validation":[77],"on":[78],"dataset":[80],"ImageCLEFmedical":[82],"2023":[83],"demonstrates":[84],"model\u2019s":[86],"prowess,":[87],"achieving":[88],"best-averaged":[90],"results":[91],"against":[92],"several":[93],"methods.":[95],"Significant":[96],"improvements":[97],"ROUGE":[99],"CIDEr":[101],"underscore":[102],"method\u2019s":[104],"efficacy,":[105],"highlighting":[106],"promising":[107],"outcomes":[108],"rapid":[111],"medical-domain":[112],"adaptation":[113],"models":[118],"addressing":[120],"posed":[122],"data":[124],"scarcity.":[125],"Our":[126],"codes":[127],"weights":[130],"are":[131],"available":[132],"at":[133],"https://openi.pcl.ac.cn/OpenMedIA/MAKEN.":[134]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}