{"id":"https://openalex.org/W4412021371","doi":"https://doi.org/10.1109/cbms65348.2025.00126","title":"Detection of Active and Latent Tuberculosis with Explainable Deep Learning Ensembles","display_name":"Detection of Active and Latent Tuberculosis with Explainable Deep Learning Ensembles","publication_year":2025,"publication_date":"2025-06-18","ids":{"openalex":"https://openalex.org/W4412021371","doi":"https://doi.org/10.1109/cbms65348.2025.00126"},"language":"en","primary_location":{"id":"doi:10.1109/cbms65348.2025.00126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbms65348.2025.00126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS)","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/A5013410051","display_name":"Lara Visu\u00f1a","orcid":"https://orcid.org/0000-0002-2944-6693"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Lara Visu\u00f1a","raw_affiliation_strings":["University Carlos III of Madrid,Computer Science Department,Leganes,Spain"],"affiliations":[{"raw_affiliation_string":"University Carlos III of Madrid,Computer Science Department,Leganes,Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089162981","display_name":"Javier Garcia\u2010Blas","orcid":"https://orcid.org/0000-0003-1452-1918"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Javier Garcia-Blas","raw_affiliation_strings":["University Carlos III of Madrid,Computer Science Department,Leganes,Spain"],"affiliations":[{"raw_affiliation_string":"University Carlos III of Madrid,Computer Science Department,Leganes,Spain","institution_ids":["https://openalex.org/I50357001"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012463690","display_name":"J. Carretero","orcid":"https://orcid.org/0000-0001-5750-2237"},"institutions":[{"id":"https://openalex.org/I50357001","display_name":"Universidad Carlos III de Madrid","ror":"https://ror.org/03ths8210","country_code":"ES","type":"education","lineage":["https://openalex.org/I50357001"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jesus Carretero","raw_affiliation_strings":["University Carlos III of Madrid,Computer Science Department,Leganes,Spain"],"affiliations":[{"raw_affiliation_string":"University Carlos III of Madrid,Computer Science Department,Leganes,Spain","institution_ids":["https://openalex.org/I50357001"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013410051"],"corresponding_institution_ids":["https://openalex.org/I50357001"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2898219,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"599","last_page":"604"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9609000086784363,"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":0.9609000086784363,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9333999752998352,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10038","display_name":"Tuberculosis Research and Epidemiology","score":0.9228000044822693,"subfield":{"id":"https://openalex.org/subfields/2725","display_name":"Infectious Diseases"},"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":0.6111372113227844},{"id":"https://openalex.org/keywords/latent-tuberculosis","display_name":"Latent tuberculosis","score":0.6106249094009399},{"id":"https://openalex.org/keywords/active-tuberculosis","display_name":"Active tuberculosis","score":0.5610149502754211},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5517206788063049},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45701295137405396},{"id":"https://openalex.org/keywords/tuberculosis","display_name":"Tuberculosis","score":0.36461734771728516},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3276655972003937},{"id":"https://openalex.org/keywords/mycobacterium-tuberculosis","display_name":"Mycobacterium tuberculosis","score":0.1932072639465332},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.09408783912658691}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6111372113227844},{"id":"https://openalex.org/C2779806340","wikidata":"https://www.wikidata.org/wiki/Q4254929","display_name":"Latent tuberculosis","level":4,"score":0.6106249094009399},{"id":"https://openalex.org/C3019041143","wikidata":"https://www.wikidata.org/wiki/Q12204","display_name":"Active tuberculosis","level":4,"score":0.5610149502754211},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5517206788063049},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45701295137405396},{"id":"https://openalex.org/C2781069245","wikidata":"https://www.wikidata.org/wiki/Q12204","display_name":"Tuberculosis","level":2,"score":0.36461734771728516},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3276655972003937},{"id":"https://openalex.org/C2777975735","wikidata":"https://www.wikidata.org/wiki/Q130971","display_name":"Mycobacterium tuberculosis","level":3,"score":0.1932072639465332},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.09408783912658691},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cbms65348.2025.00126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cbms65348.2025.00126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 38th International Symposium on Computer-Based Medical Systems (CBMS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W2101234009","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2962858109","https://openalex.org/W2966747454","https://openalex.org/W3034922525","https://openalex.org/W3036909266","https://openalex.org/W3083753334","https://openalex.org/W4225005315","https://openalex.org/W4300817322","https://openalex.org/W4306248755","https://openalex.org/W4306291733","https://openalex.org/W4384831205","https://openalex.org/W4389832953","https://openalex.org/W4396227690","https://openalex.org/W4403128491","https://openalex.org/W4405660025"],"related_works":["https://openalex.org/W2412323770","https://openalex.org/W2123708792","https://openalex.org/W4298140190","https://openalex.org/W2956144804","https://openalex.org/W3036655379","https://openalex.org/W3200000059","https://openalex.org/W4380075502","https://openalex.org/W2373695084","https://openalex.org/W4389030982","https://openalex.org/W2124875533"],"abstract_inverted_index":{"Tuberculosis":[0],"is":[1,22,41,66,69],"one":[2,95],"of":[3,15,56,110,138,170,173,205,217,227,239],"the":[4,8,13,38,54,83,90,94,135,143,161,171,174,198,211,215,218,222,225,228,235,240],"deadliest":[5],"diseases":[6,157],"in":[7,142,187,242],"world,":[9],"despite":[10],"being":[11,128],"treatable,":[12],"number":[14,137],"new":[16,48],"cases":[17,34],"increases":[18],"yearly.":[19],"The":[20,122,145,179,200],"situation":[21],"even":[23],"more":[24],"concerning":[25],"due":[26,133],"to":[27,46,72,82,115,126,134,149,166,196],"antimicrobial":[28],"resistance":[29],"(AMR).":[30],"To":[31],"avoid":[32],"undetected":[33],"and":[35,49,59,155,237],"breaking":[36],"transmission,":[37],"research":[39],"community":[40],"using":[42],"artificial":[43],"intelligence":[44],"(AI)":[45],"develop":[47],"fast":[50],"diagnosis":[51],"tools.":[52],"Nevertheless,":[53],"creation":[55],"good":[57],"quality":[58],"well-balanced":[60],"datasets":[61],"for":[62],"training":[63],"AI":[64],"tools":[65],"challenging.":[67],"It":[68],"especially":[70],"difficult":[71],"collect":[73],"data":[74,132],"on":[75],"asymptomatic":[76],"patients":[77,140,154,169],"who":[78,96],"do":[79,87],"not":[80,88],"go":[81],"professional":[84],"as":[85,93,160,165],"they":[86],"feel":[89],"symptoms,":[91],"such":[92],"suffered":[97],"latent":[98,139],"tuberculosis.":[99],"In":[100],"this":[101],"work,":[102],"we":[103],"propose":[104],"an":[105,188],"explainable":[106],"deep":[107],"learning":[108],"ensemble":[109,123,189,212],"convolutional":[111],"neural":[112],"networks":[113],"(CNNs)":[114],"classify":[116],"tuberculosis":[117,151,168],"chest":[118],"X-ray":[119],"(CXRs)":[120],"images.":[121],"was":[124,147,181],"designed":[125,182],"alleviate":[127],"influenced":[129],"by":[130,231],"unbalanced":[131],"small":[136],"included":[141],"dataset.":[144],"system":[146,201,229,241],"trained":[148],"detect":[150],"against":[152],"healthy":[153],"other":[156],"with":[158,183],"CXRs":[159],"only":[162],"input,":[163],"so":[164],"inform":[167],"stage":[172],"disease":[175],"(active":[176],"or":[177],"latent).":[178],"model":[180],"two":[184],"parallel":[185],"CNNs":[186],"that":[190,210],"used":[191],"a":[192,203],"random":[193],"forest":[194],"(RF)":[195],"overcome":[197],"imbalance.":[199],"reported":[202],"performance":[204,216],"96":[206],"%":[207],"accuracy,":[208],"showing":[209],"can":[213],"improve":[214],"underrepresented":[219],"class.":[220],"Further,":[221],"RF":[223],"completed":[224],"interpretability":[226],"provided":[230],"grad-CAM":[232],"heatmaps,":[233],"supporting":[234],"evolution":[236],"integration":[238],"clinical":[243],"environments.":[244]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
