{"id":"https://openalex.org/W4404029899","doi":"https://doi.org/10.1109/icccnt61001.2024.10726043","title":"Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer","display_name":"Deep Ensembling with Multimodal Image Fusion for Efficient Classification of Lung Cancer","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4404029899","doi":"https://doi.org/10.1109/icccnt61001.2024.10726043"},"language":"en","primary_location":{"id":"doi:10.1109/icccnt61001.2024.10726043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10726043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2502.00078","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018310642","display_name":"Surochita Pal","orcid":null},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Surochita Pal","raw_affiliation_strings":["Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India,700108"],"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India,700108","institution_ids":["https://openalex.org/I6498739"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028039397","display_name":"Sushmita Mitra","orcid":"https://orcid.org/0000-0001-9285-1117"},"institutions":[{"id":"https://openalex.org/I6498739","display_name":"Indian Statistical Institute","ror":"https://ror.org/00q2w1j53","country_code":"IN","type":"education","lineage":["https://openalex.org/I6498739"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sushmita Mitra","raw_affiliation_strings":["Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India,700108"],"affiliations":[{"raw_affiliation_string":"Indian Statistical Institute,Machine Intelligence Unit,Kolkata,India,700108","institution_ids":["https://openalex.org/I6498739"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5018310642"],"corresponding_institution_ids":["https://openalex.org/I6498739"],"apc_list":null,"apc_paid":null,"fwci":0.8061,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.75328088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9977999925613403,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9977999925613403,"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/T10202","display_name":"Lung Cancer Diagnosis and Treatment","score":0.996399998664856,"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/T10862","display_name":"AI in cancer detection","score":0.9855999946594238,"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/computer-science","display_name":"Computer science","score":0.6377564072608948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6238305568695068},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.48981210589408875},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4768993854522705},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4644581973552704},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3856261074542999},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37517714500427246},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.0535663366317749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6377564072608948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6238305568695068},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.48981210589408875},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4768993854522705},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4644581973552704},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3856261074542999},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37517714500427246},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0535663366317749},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icccnt61001.2024.10726043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccnt61001.2024.10726043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2502.00078","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.00078","pdf_url":"https://arxiv.org/pdf/2502.00078","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2502.00078","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2502.00078","pdf_url":"https://arxiv.org/pdf/2502.00078","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.5699999928474426,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404029899.pdf","grobid_xml":"https://content.openalex.org/works/W4404029899.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2047572918","https://openalex.org/W2194775991","https://openalex.org/W2531409750","https://openalex.org/W2738392531","https://openalex.org/W2787890383","https://openalex.org/W2820787630","https://openalex.org/W2895328943","https://openalex.org/W2919115771","https://openalex.org/W2953830169","https://openalex.org/W2962858109","https://openalex.org/W2990253461","https://openalex.org/W3007920826","https://openalex.org/W3015282954","https://openalex.org/W3106286734","https://openalex.org/W3155032836","https://openalex.org/W3166233244","https://openalex.org/W4236325002","https://openalex.org/W4246193833","https://openalex.org/W4282915171","https://openalex.org/W4385708469","https://openalex.org/W6637373629"],"related_works":["https://openalex.org/W2788731446","https://openalex.org/W2204403038","https://openalex.org/W3152170969","https://openalex.org/W2379054866","https://openalex.org/W2370195708","https://openalex.org/W1490651872","https://openalex.org/W2139242969","https://openalex.org/W2284201331","https://openalex.org/W2095903272","https://openalex.org/W1989561795"],"abstract_inverted_index":{"This":[0],"study":[1],"focuses":[2],"on":[3,133],"the":[4,19,35,67,80,87,98,106,134,146,149],"classification":[5,81],"of":[6,37,83,108,148],"cancerous":[7],"and":[8,25,39,48,140],"healthy":[9],"slices":[10],"from":[11],"multimodal":[12],"lung":[13],"images.":[14,30,85],"The":[15,31,101,116,128,142],"data":[16,110],"used":[17],"in":[18,111],"research":[20],"comprises":[21],"Computed":[22],"Tomography":[23,28],"(CT)":[24],"Positron":[26],"Emission":[27],"(PET)":[29],"proposed":[32,117,150],"strategy":[33,95],"achieves":[34],"fusion":[36],"PET":[38],"CT":[40],"images":[41,69],"by":[42],"utilizing":[43],"Principal":[44],"Component":[45],"Analysis":[46],"(PCA)":[47],"an":[49],"Autoencoder.":[50],"Subsequently,":[51],"a":[52,91],"new":[53],"ensemble-based":[54],"classifier":[55],"developed,":[56],"Deep":[57],"Ensembled":[58],"Multimodal":[59],"Fusion":[60],"(DEMF),":[61],"employing":[62],"majority":[63],"voting":[64],"to":[65,78],"classify":[66],"sample":[68,89],"under":[70],"examination.":[71],"Gradient-weighted":[72],"Class":[73],"Activation":[74],"Mapping":[75],"(Grad-CAM)":[76],"employed":[77,96],"visualize":[79],"accuracy":[82],"cancer-affected":[84],"Given":[86],"limited":[88],"size,":[90],"random":[92],"image":[93,114],"augmentation":[94],"during":[97],"training":[99],"phase.":[100],"DEMF":[102],"network":[103,118,129],"helps":[104],"mitigate":[105],"challenges":[107],"scarce":[109],"computer-aided":[112],"medical":[113],"analysis.":[115],"compared":[119],"with":[120],"state-of-the-art":[121],"networks":[122],"across":[123],"three":[124],"publicly":[125],"available":[126],"datasets.":[127],"outperforms":[130],"others":[131],"based":[132],"metrics":[135],"-":[136],"Accuracy,":[137],"F1Score,":[138],"Precision,":[139],"Recall.":[141],"investigation":[143],"results":[144],"highlight":[145],"effectiveness":[147],"network.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
