{"id":"https://openalex.org/W7127592296","doi":"https://doi.org/10.1109/dese68208.2025.11368210","title":"Explainable AI for Chest X-Rays: Combining Grad-CAM and LLMS for Improved Diagnosis","display_name":"Explainable AI for Chest X-Rays: Combining Grad-CAM and LLMS for Improved Diagnosis","publication_year":2025,"publication_date":"2025-11-10","ids":{"openalex":"https://openalex.org/W7127592296","doi":"https://doi.org/10.1109/dese68208.2025.11368210"},"language":null,"primary_location":{"id":"doi:10.1109/dese68208.2025.11368210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dese68208.2025.11368210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 18th International Conference on Development in eSystem Engineering (DeSE)","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/A5125007897","display_name":"Ayodele Kolawole","orcid":null},"institutions":[{"id":"https://openalex.org/I874055015","display_name":"Teesside University","ror":"https://ror.org/03z28gk75","country_code":"GB","type":"education","lineage":["https://openalex.org/I874055015"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Ayodele Kolawole","raw_affiliation_strings":["School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK","institution_ids":["https://openalex.org/I874055015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019082308","display_name":"Ndidi Bianca Ogbo","orcid":"https://orcid.org/0009-0006-1814-1428"},"institutions":[{"id":"https://openalex.org/I874055015","display_name":"Teesside University","ror":"https://ror.org/03z28gk75","country_code":"GB","type":"education","lineage":["https://openalex.org/I874055015"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Ndidi Bianca Ogbo","raw_affiliation_strings":["School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK","institution_ids":["https://openalex.org/I874055015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125060605","display_name":"Mansha Nawaz","orcid":null},"institutions":[{"id":"https://openalex.org/I874055015","display_name":"Teesside University","ror":"https://ror.org/03z28gk75","country_code":"GB","type":"education","lineage":["https://openalex.org/I874055015"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Mansha Nawaz","raw_affiliation_strings":["School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK","institution_ids":["https://openalex.org/I874055015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125042192","display_name":"Shatha Ghareeb","orcid":null},"institutions":[{"id":"https://openalex.org/I874055015","display_name":"Teesside University","ror":"https://ror.org/03z28gk75","country_code":"GB","type":"education","lineage":["https://openalex.org/I874055015"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Shatha Ghareeb","raw_affiliation_strings":["School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing, Engineering &amp; Digital Technologies, Teesside University,Middlesbrough,UK","institution_ids":["https://openalex.org/I874055015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035982173","display_name":"Jamila Mustafina","orcid":"https://orcid.org/0000-0001-5770-4111"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Jamila Mustafina","raw_affiliation_strings":["Kazan Federal University,Kazan,Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan Federal University,Kazan,Russia","institution_ids":["https://openalex.org/I21203515"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5125007897"],"corresponding_institution_ids":["https://openalex.org/I874055015"],"apc_list":null,"apc_paid":null,"fwci":1.1271,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.84565009,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"505","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.8047999739646912,"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":0.8047999739646912,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.0430000014603138,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.026399999856948853,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"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/interpretability","display_name":"Interpretability","score":0.8464000225067139},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.6439999938011169},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5842999815940857},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.578000009059906},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5333999991416931},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46889999508857727},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4120999872684479}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8464000225067139},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.6439999938011169},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5842999815940857},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.578000009059906},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5333999991416931},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5267000198364258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5080000162124634},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46889999508857727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4189999997615814},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4120999872684479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38999998569488525},{"id":"https://openalex.org/C2781137159","wikidata":"https://www.wikidata.org/wiki/Q1283318","display_name":"Chest radiograph","level":3,"score":0.34529998898506165},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3192000091075897},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C19527891","wikidata":"https://www.wikidata.org/wiki/Q1120908","display_name":"Medical physics","level":1,"score":0.3158999979496002},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C197947376","wikidata":"https://www.wikidata.org/wiki/Q5155608","display_name":"Comparability","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C2989236134","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Patient care","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.2687999904155731},{"id":"https://openalex.org/C2780910867","wikidata":"https://www.wikidata.org/wiki/Q1952416","display_name":"Multimodality","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dese68208.2025.11368210","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dese68208.2025.11368210","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 18th International Conference on Development in eSystem Engineering (DeSE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.448292076587677,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2130147855","https://openalex.org/W2194775991","https://openalex.org/W2253429366","https://openalex.org/W2611650229","https://openalex.org/W2907760128","https://openalex.org/W2957177432","https://openalex.org/W2962858109","https://openalex.org/W2963446712","https://openalex.org/W3168796319","https://openalex.org/W4387241304","https://openalex.org/W4393993698","https://openalex.org/W4394014083","https://openalex.org/W4399953622","https://openalex.org/W4401397810","https://openalex.org/W4402524908","https://openalex.org/W4408141508"],"related_works":[],"abstract_inverted_index":{"Chest":[0],"radiographs":[1],"(CXRs)":[2],"remain":[3],"one":[4],"of":[5,23,87,101,106,114],"the":[6,84,119],"most":[7],"widely":[8],"used":[9],"imaging":[10,18],"modalities":[11],"for":[12,75],"diagnosing":[13],"cardiopulmonary":[14],"diseases,":[15],"yet":[16],"increasing":[17],"demand":[19],"and":[20,30,103,130,133,152,159,171,188],"a":[21,52,66,95,177],"shortage":[22],"radiologists":[24],"continue":[25],"to":[26,65,156,182],"challenge":[27],"diagnostic":[28,144,186],"accuracy":[29],"efficiency.":[31],"Deep":[32],"learning":[33],"approaches":[34],"offer":[35],"promising":[36],"solutions,":[37],"but":[38],"their":[39],"clinical":[40,126,160,193],"adoption":[41],"is":[42],"hindered":[43],"by":[44],"limited":[45],"interpretability.":[46],"In":[47,117],"this":[48],"study,":[49],"we":[50],"compare":[51],"baseline":[53,80],"convolutional":[54],"neural":[55],"network":[56],"(CNN)":[57],"augmented":[58],"with":[59,108,125],"Gradient-weighted":[60],"Class":[61],"Activation":[62],"Mapping":[63],"(Grad-CAM)":[64],"multimodal":[67,120,166],"framework":[68,121],"that":[69,165],"integrates":[70],"large":[71],"language":[72],"models":[73],"(LLMs)":[74],"explainable":[76],"CXR":[77],"interpretation.":[78],"The":[79],"CNN,":[81],"trained":[82],"on":[83,136],"ChestX-ray8":[85],"dataset":[86],"108,848":[88],"images":[89],"across":[90],"14":[91],"thoracic":[92],"pathologies,":[93],"achieved":[94],"mean":[96],"Area":[97],"under":[98],"Curve":[99],"(AUC)":[100],"0.891":[102],"macro":[104],"F1-score":[105],"0.80,":[107],"Grad-CAM":[109],"heatmaps":[110],"providing":[111],"visual":[112],"explanations":[113],"model":[115],"predictions.":[116],"contrast,":[118],"combined":[122],"CNN-derived":[123],"features":[124,155],"narratives":[127],"using":[128],"cross-attention":[129],"fewshot":[131],"prompting":[132],"was":[134],"fine-tuned":[135],"68,000":[137],"paired":[138],"image-report":[139],"samples.":[140],"This":[141],"approach":[142],"improved":[143],"performance":[145],"(AUC=0.915,":[146],"F":[147],"1=0.89),":[148],"generated":[149],"human-readable":[150],"reports,":[151],"localized":[153],"anatomical":[154],"enhance":[157],"interpretability":[158],"reasoning.":[161],"Our":[162],"findings":[163],"demonstrate":[164],"AI":[167],"substantially":[168],"improves":[169],"precision":[170],"transparency":[172],"over":[173],"CNN-only":[174],"systems,":[175],"offering":[176],"more":[178],"reliable":[179],"decision-support":[180],"tool":[181],"assist":[183],"radiologists,":[184],"reduce":[185],"errors,":[187],"optimize":[189],"workflow":[190],"in":[191],"high-volume":[192],"environments.":[194]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-20T08:49:12.498775","created_date":"2026-02-06T00:00:00"}
