{"id":"https://openalex.org/W4406259733","doi":"https://doi.org/10.1109/bibm62325.2024.10822172","title":"Addressing Class Imbalance with Latent Diffusion-based Data Augmentation for Improving Disease Classification in Pediatric Chest X-rays","display_name":"Addressing Class Imbalance with Latent Diffusion-based Data Augmentation for Improving Disease Classification in Pediatric Chest X-rays","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4406259733","doi":"https://doi.org/10.1109/bibm62325.2024.10822172","pmid":"https://pubmed.ncbi.nlm.nih.gov/40134830"},"language":"en","primary_location":{"id":"doi:10.1109/bibm62325.2024.10822172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822172","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":"conference-paper","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11936509/pdf/nihms-2041958.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017208524","display_name":"Sivaramakrishnan Rajaraman","orcid":"https://orcid.org/0000-0003-0871-8634"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sivaramakrishnan Rajaraman","raw_affiliation_strings":["National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004135809","display_name":"Zhaohui Liang","orcid":"https://orcid.org/0000-0002-9361-5535"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaohui Liang","raw_affiliation_strings":["National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018828944","display_name":"Zhiyun Xue","orcid":"https://orcid.org/0000-0003-0644-385X"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhiyun Xue","raw_affiliation_strings":["National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073995883","display_name":"Sameer Antani","orcid":"https://orcid.org/0000-0002-0040-1387"},"institutions":[{"id":"https://openalex.org/I1299303238","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88","country_code":"US","type":"government","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238"]},{"id":"https://openalex.org/I2800548410","display_name":"United States National Library of Medicine","ror":"https://ror.org/0060t0j89","country_code":"US","type":"archive","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sameer Antani","raw_affiliation_strings":["National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institutes of Health,Division of Intramural Research National Library of Medicine,MD,USA","institution_ids":["https://openalex.org/I1299303238","https://openalex.org/I2800548410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1875,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.9602198,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"2024","issue":null,"first_page":"5059","last_page":"5066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9973000288009644,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9973000288009644,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/computer-science","display_name":"Computer science","score":0.563764750957489},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.5041681528091431},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5000865459442139},{"id":"https://openalex.org/keywords/latent-class-model","display_name":"Latent class model","score":0.4116136133670807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3037329912185669},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23426324129104614},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1289224624633789}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.563764750957489},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.5041681528091431},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5000865459442139},{"id":"https://openalex.org/C70727504","wikidata":"https://www.wikidata.org/wiki/Q1806878","display_name":"Latent class model","level":2,"score":0.4116136133670807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3037329912185669},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23426324129104614},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1289224624633789},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bibm62325.2024.10822172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm62325.2024.10822172","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"},{"id":"pmid:40134830","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40134830","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Bioinformatics and Biomedicine","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11936509","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11936509","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11936509/pdf/nihms-2041958.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings (IEEE Int Conf Bioinformatics Biomed)","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:11936509","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11936509","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11936509/pdf/nihms-2041958.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings (IEEE Int Conf Bioinformatics Biomed)","raw_type":"Text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G202981822","display_name":null,"funder_award_id":"Z99 LM999999","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G2261204241","display_name":null,"funder_award_id":"ZIA LM010018","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337372","display_name":"U.S. National Library of Medicine","ror":"https://ror.org/0060t0j89"},{"id":"https://openalex.org/F4320338440","display_name":"HORIZON EUROPE Health","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406259733.pdf","grobid_xml":"https://content.openalex.org/works/W4406259733.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W1904878066","https://openalex.org/W2057493527","https://openalex.org/W2142514727","https://openalex.org/W2183341477","https://openalex.org/W2592929672","https://openalex.org/W2611650229","https://openalex.org/W2788633781","https://openalex.org/W2954996726","https://openalex.org/W2963466845","https://openalex.org/W2979940322","https://openalex.org/W2995225687","https://openalex.org/W3101156210","https://openalex.org/W3147783603","https://openalex.org/W3207796226","https://openalex.org/W4205312762","https://openalex.org/W4224308287","https://openalex.org/W4310269372","https://openalex.org/W4312749295","https://openalex.org/W4312933868","https://openalex.org/W4322769152","https://openalex.org/W4324090966","https://openalex.org/W4367173928","https://openalex.org/W4386072096","https://openalex.org/W4386305288","https://openalex.org/W4389429156","https://openalex.org/W4402727293","https://openalex.org/W6840155194","https://openalex.org/W6846988067","https://openalex.org/W6852670835","https://openalex.org/W6861037531"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)":[2],"has":[3,31],"transformed":[4],"medical":[5,81,224],"image":[6,36,225],"classification;":[7],"however,":[8],"its":[9],"efficacy":[10],"is":[11,151,173,215],"often":[12],"limited":[13],"by":[14,114],"significant":[15],"data":[16,58,122,156,210],"imbalance":[17,222],"due":[18],"to":[19,26,44,63,105,139],"far":[20],"fewer":[21],"cases":[22],"(minority":[23],"class)":[24],"compared":[25,174],"controls":[27],"(majority":[28],"class).":[29],"It":[30],"been":[32],"shown":[33,76],"that":[34,50,158,195,209],"synthetic":[35],"augmentation":[37,197,211],"techniques":[38],"can":[39],"simulate":[40],"clinical":[41],"variability,":[42],"leading":[43],"enhanced":[45],"model":[46,119,150],"performance.":[47,108,192],"We":[48,109],"hypothesize":[49],"they":[51],"could":[52],"also":[53],"mitigate":[54],"the":[55,64,86,190,196],"challenge":[56],"of":[57,88,144,165],"imbalance,":[59],"thereby":[60],"addressing":[61,220],"overfitting":[62],"majority":[65],"class":[66,221],"and":[67,99,128,146,168,186,203],"enhancing":[68],"generalization.":[69],"Recently,":[70],"latent":[71],"diffusion":[72],"models":[73],"(LDMs)":[74],"have":[75],"promise":[77],"in":[78,93,223],"synthesizing":[79,94],"high-quality":[80],"images.":[82],"This":[83],"study":[84],"evaluates":[85],"effectiveness":[87],"a":[89,101],"text-guided":[90,136],"image-to-image":[91,137],"LDM":[92],"disease-positive":[95],"chest":[96],"X-rays":[97],"(CXRs)":[98],"augmenting":[100],"pediatric":[102],"CXR":[103],"dataset":[104],"improve":[106],"classification":[107],"first":[110],"establish":[111],"baseline":[112,191],"performance":[113,172],"fine-tuning":[115],"an":[116,154,216],"ImageNet-pretrained":[117],"Inception-V3":[118,149],"on":[120,153],"class-imbalanced":[121],"for":[123,219],"two":[124],"tasks-normal":[125],"vs.":[126,130],"pneumonia":[127,145],"normal":[129],"bronchopneumonia.":[131,147],"Next,":[132],"we":[133],"fine-tune":[134],"individual":[135],"LDMs":[138],"generate":[140],"CXRs":[141],"showing":[142],"signs":[143],"The":[148],"retrained":[152],"updated":[155],"set":[157],"includes":[159],"these":[160],"synthesized":[161],"images":[162,214],"as":[163],"part":[164],"augmented":[166],"training":[167],"validation":[169],"sets.":[170],"Classification":[171],"using":[175,212],"balanced":[176],"accuracy,":[177],"sensitivity,":[178],"specificity,":[179],"F-score,":[180],"Matthews":[181],"correlation":[182],"coefficient":[183],"(MCC),":[184],"Kappa,":[185],"Youden's":[187,200],"index":[188,201],"against":[189],"Results":[193],"show":[194],"significantly":[198],"improves":[199],"(p<0.05)":[202],"markedly":[204],"enhances":[205],"other":[206],"metrics,":[207],"indicating":[208],"LDM-synthesized":[213],"effective":[217],"strategy":[218],"classification.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
