{"id":"https://openalex.org/W4391331110","doi":"https://doi.org/10.1145/3634875.3634877","title":"Shared Embedding of X-ray & Enose Networks for Lung Cancer Classification","display_name":"Shared Embedding of X-ray & Enose Networks for Lung Cancer Classification","publication_year":2023,"publication_date":"2023-10-20","ids":{"openalex":"https://openalex.org/W4391331110","doi":"https://doi.org/10.1145/3634875.3634877"},"language":"en","primary_location":{"id":"doi:10.1145/3634875.3634877","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3634875.3634877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing","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/A5041090755","display_name":"H.H. Liao","orcid":"https://orcid.org/0009-0000-1321-2211"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Hung-Ju Liao","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071316954","display_name":"Ya-Chu Hsieh","orcid":"https://orcid.org/0000-0002-0266-0286"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ya-Chu Hsieh","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103253465","display_name":"Shih-Wen Chiu","orcid":"https://orcid.org/0009-0000-5093-8492"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shih-Wen Chiu","raw_affiliation_strings":["Enosim Bio-Tech, Taiwan"],"affiliations":[{"raw_affiliation_string":"Enosim Bio-Tech, Taiwan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078713318","display_name":"Meng\u2010Rui Lee","orcid":"https://orcid.org/0000-0002-7220-4833"},"institutions":[{"id":"https://openalex.org/I4210131804","display_name":"National Taiwan University Hospital","ror":"https://ror.org/03nteze27","country_code":"TW","type":"healthcare","lineage":["https://openalex.org/I4210131804"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Meng-Rui Lee","raw_affiliation_strings":["National Taiwan University Hospital, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Taiwan University Hospital, Taiwan","institution_ids":["https://openalex.org/I4210131804"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044259295","display_name":"Kea\u2010Tiong Tang","orcid":"https://orcid.org/0000-0002-9689-1236"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Kea-Tiong Tang","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102008600","display_name":"Min Sun","orcid":"https://orcid.org/0000-0001-9598-8178"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Min Sun","raw_affiliation_strings":["National Tsing Hua University, Taiwan"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Taiwan","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5041090755"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.40107666,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9991000294685364,"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6374571323394775},{"id":"https://openalex.org/keywords/lung-cancer","display_name":"Lung cancer","score":0.466054767370224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4559297263622284},{"id":"https://openalex.org/keywords/optoelectronics","display_name":"Optoelectronics","score":0.40576305985450745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32088780403137207},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.3071475028991699},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.26077699661254883},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.23656773567199707}],"concepts":[{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6374571323394775},{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.466054767370224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4559297263622284},{"id":"https://openalex.org/C49040817","wikidata":"https://www.wikidata.org/wiki/Q193091","display_name":"Optoelectronics","level":1,"score":0.40576305985450745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32088780403137207},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.3071475028991699},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.26077699661254883},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.23656773567199707}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3634875.3634877","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3634875.3634877","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 8th International Conference on Biomedical Imaging, Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[{"id":"https://openalex.org/G7010653464","display_name":null,"funder_award_id":"110F7MAHE1","funder_id":"https://openalex.org/F4320323817","funder_display_name":"Universitas Brawijaya"}],"funders":[{"id":"https://openalex.org/F4320323817","display_name":"Universitas Brawijaya","ror":"https://ror.org/01wk3d929"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2142514727","https://openalex.org/W2611650229","https://openalex.org/W2904183610","https://openalex.org/W2914203365","https://openalex.org/W2949301588","https://openalex.org/W2979847946","https://openalex.org/W2990307191","https://openalex.org/W3099647611","https://openalex.org/W3101156210","https://openalex.org/W3101520758","https://openalex.org/W3135367836","https://openalex.org/W3147142721","https://openalex.org/W3196927126","https://openalex.org/W3198028910","https://openalex.org/W3216275916"],"related_works":["https://openalex.org/W4246450666","https://openalex.org/W4388998267","https://openalex.org/W2898370298","https://openalex.org/W4390401159","https://openalex.org/W2744391499","https://openalex.org/W3120461830","https://openalex.org/W4230250635","https://openalex.org/W3041790586","https://openalex.org/W2018879842","https://openalex.org/W3144504424"],"abstract_inverted_index":{"Lung":[0],"cancer":[1],"is":[2,21,117],"a":[3,57,181],"significant":[4],"cause":[5],"of":[6,30,86],"cancer-related":[7],"deaths":[8],"globally.":[9],"X-ray":[10,160],"image":[11,77,96,111],"has":[12],"been":[13],"widely":[14,24],"used":[15,46],"for":[16,47],"first-stage":[17,49],"screening":[18,50],"as":[19],"it":[20],"affordable":[22],"and":[23,63,79,127,151,162,168,180],"available.":[25],"Recently,":[26],"with":[27,137],"the":[28,31,48,52,76,80,84,87,94,100,106,110,142,145,153,157,172,187,196],"development":[29],"gas":[32],"sensor":[33],"IC":[34],"chip,":[35],"low-cost":[36],"enose":[37,64,81,88,101,163],"sensing":[38],"exhaled":[39],"breath":[40],"from":[41],"patients":[42],"can":[43],"potentially":[44],"be":[45,120],"in":[51],"near":[53],"future.":[54],"We":[55],"propose":[56],"share-embedding":[58,115],"model":[59,72,97,112,116,143],"combining":[60],"x-ray":[61],"images":[62,161],"sensory":[65],"signals":[66],"to":[67,92,98,103,119,122,140,144],"diagnose":[68],"lung":[69],"cancer.":[70],"Our":[71,114],"contains":[73],"two":[74],"branches:":[75],"branch":[78,102,179],"branch.":[82],"Since":[83],"lack":[85],"data,":[89],"we":[90,133,155],"try":[91],"use":[93,134],"pretrained":[95],"guide":[99],"align":[104],"toward":[105],"embedding":[107],"space":[108],"that":[109],"learned.":[113],"designed":[118],"robust":[121],"domain":[123],"shifts":[124],"across":[125,165],"devices":[126,167],"environments.":[128,170],"To":[129,149],"further":[130],"improve":[131],"performance,":[132,154],"semi-supervised":[135,193],"learning":[136,194],"instance":[138],"weighting":[139],"transfer":[141],"unlabeled":[146],"target":[147],"domain.":[148],"train":[150],"evaluate":[152],"collect":[156],"first":[158],"paired":[159],"data":[164],"multiple":[166],"clinical":[169],"In":[171,186],"experiments,":[173],"our":[174,190],"method":[175,191],"outperforms":[176],"each":[177],"individual":[178],"feature":[182],"concatenation":[183],"fusion":[184],"method.":[185],"cross-device":[188],"setting,":[189],"leveraging":[192],"achieves":[195],"best":[197],"performance.":[198]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}