{"id":"https://openalex.org/W4405934115","doi":"https://doi.org/10.1109/access.2024.3524564","title":"An Empirical Analysis of Transformer-Based and Convolutional Neural Network Approaches for Early Detection and Diagnosis of Cancer Using Multimodal Imaging and Genomic Data","display_name":"An Empirical Analysis of Transformer-Based and Convolutional Neural Network Approaches for Early Detection and Diagnosis of Cancer Using Multimodal Imaging and Genomic Data","publication_year":2024,"publication_date":"2024-12-31","ids":{"openalex":"https://openalex.org/W4405934115","doi":"https://doi.org/10.1109/access.2024.3524564"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3524564","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3524564","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3524564","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028127854","display_name":"S Sangeetha","orcid":"https://orcid.org/0000-0002-6927-6916"},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"S. K. B. Sangeetha","raw_affiliation_strings":["Department of Computer Science and Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, Tamil Nadu, India"],"raw_orcid":"https://orcid.org/0000-0002-6927-6916","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, Tamil Nadu, India","institution_ids":["https://openalex.org/I145286018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004069904","display_name":"Sandeep Kumar Mathivanan","orcid":"https://orcid.org/0000-0001-8572-1197"},"institutions":[{"id":"https://openalex.org/I155125381","display_name":"Galgotias University","ror":"https://ror.org/02w8ba206","country_code":"IN","type":"education","lineage":["https://openalex.org/I155125381"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sandeep Kumar Mathivanan","raw_affiliation_strings":["School of Computer Science and Engineering, Galgotias University, Greater Noida, India"],"raw_orcid":"https://orcid.org/0000-0001-8572-1197","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Galgotias University, Greater Noida, India","institution_ids":["https://openalex.org/I155125381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043085840","display_name":"V. Muthukumaran","orcid":null},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Muthukumaran","raw_affiliation_strings":["Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, College of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, Chennai, India","institution_ids":["https://openalex.org/I145286018"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000042272","display_name":"Jaehyuk Cho","orcid":"https://orcid.org/0000-0002-9113-6805"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jaehyuk Cho","raw_affiliation_strings":["Department of Software Engineering and Division of Electronics and Information Engineering, Jeonbuk National University, Jeonju-si, Republic of Korea","Department of Software Engineering & Division of Electronics and Information Engineering, Jeonbuk National University, Jeonju-si, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-9113-6805","affiliations":[{"raw_affiliation_string":"Department of Software Engineering and Division of Electronics and Information Engineering, Jeonbuk National University, Jeonju-si, Republic of Korea","institution_ids":["https://openalex.org/I80611190"]},{"raw_affiliation_string":"Department of Software Engineering & Division of Electronics and Information Engineering, Jeonbuk National University, Jeonju-si, Republic of Korea","institution_ids":["https://openalex.org/I80611190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066276015","display_name":"V E Sathishkumar","orcid":"https://orcid.org/0000-0002-8271-2022"},"institutions":[{"id":"https://openalex.org/I84339108","display_name":"Sunway University","ror":"https://ror.org/04mjt7f73","country_code":"MY","type":"education","lineage":["https://openalex.org/I84339108"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"and Sathishkumar Veerappampalayam Easwaramoorthy","raw_affiliation_strings":["School of Engineering and Technology, Sunway University, Petaling Jaya, Selangor Darul Ehsan, Malaysia","Department of Computing and Information Systems, Sunway University, Petaling Jaya, Selangor Daru, Malaysia"],"raw_orcid":"https://orcid.org/0000-0002-8271-2022","affiliations":[{"raw_affiliation_string":"School of Engineering and Technology, Sunway University, Petaling Jaya, Selangor Darul Ehsan, Malaysia","institution_ids":["https://openalex.org/I84339108"]},{"raw_affiliation_string":"Department of Computing and Information Systems, Sunway University, Petaling Jaya, Selangor Daru, Malaysia","institution_ids":["https://openalex.org/I84339108"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.9711,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.94555228,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"13","issue":null,"first_page":"6120","last_page":"6145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.44359999895095825,"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"}},"topics":[{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.44359999895095825,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.74062180519104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6975700855255127},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5136096477508545},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.44472020864486694},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42761799693107605},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07358372211456299}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.74062180519104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6975700855255127},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5136096477508545},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.44472020864486694},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42761799693107605},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07358372211456299},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3524564","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3524564","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:691afbba75b841f7911617605882e08a","is_oa":true,"landing_page_url":"https://doaj.org/article/691afbba75b841f7911617605882e08a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 6120-6145 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3524564","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3524564","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2304258614","https://openalex.org/W2983981789","https://openalex.org/W3012470135","https://openalex.org/W3019898597","https://openalex.org/W3039337614","https://openalex.org/W3092071943","https://openalex.org/W3106717751","https://openalex.org/W3189278858","https://openalex.org/W3191603129","https://openalex.org/W4220903131","https://openalex.org/W4224215508","https://openalex.org/W4307727479","https://openalex.org/W4309478090","https://openalex.org/W4311899170","https://openalex.org/W4313531172","https://openalex.org/W4313650905","https://openalex.org/W4317930192","https://openalex.org/W4318754985","https://openalex.org/W4321500222","https://openalex.org/W4327624186","https://openalex.org/W4362580823","https://openalex.org/W4366251167","https://openalex.org/W4383558369","https://openalex.org/W4383695111","https://openalex.org/W4385201870","https://openalex.org/W4385610840","https://openalex.org/W4385813064","https://openalex.org/W4385819962","https://openalex.org/W4386137901","https://openalex.org/W4387528685","https://openalex.org/W4388092242","https://openalex.org/W4389611927","https://openalex.org/W4391107757","https://openalex.org/W4401607294"],"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/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Early":[0],"diagnosis":[1,32],"of":[2,9,22,64,72,85,92,145,152,215,218,280],"cancer":[3,31,248,275],"has":[4,253],"focused":[5],"on":[6],"the":[7,20,45,65,123,129,177,180,184,213,216],"use":[8],"advanced":[10],"algorithms":[11,287],"to":[12,35,78,97,137,147,154,296],"achieve":[13],"accurate":[14,270],"diagnosis.":[15,276],"The":[16,41,113,234],"proposed":[17,130],"study":[18,252],"assesses":[19],"effectiveness":[21],"Transformer-based":[23],"models":[24,115],"and":[25,38,57,87,105,122,142,149,163,186,201,232,240,271,288],"Convolutional":[26],"Neural":[27],"Networks":[28],"(CNN)":[29],"in":[30,83,90,247,274,292],"with":[33,49,76,133,196,206,212,229,264],"respect":[34,77],"multimodal":[36,131],"imaging":[37,56],"genomic":[39,58],"data.":[40],"performance":[42,228],"comparisons":[43],"between":[44,140,199],"two":[46],"algorithmic":[47],"methods":[48,259],"such":[50,99],"complex":[51],"datasets,":[52],"which":[53],"combine":[54],"multi-modal":[55,265],"information,":[59],"are":[60,189,222],"presented.":[61],"In":[62,156],"search":[63],"optimal":[66],"neural":[67],"network":[68],"configuration,":[69],"a":[70,244],"series":[71],"experiments":[73],"were":[74,116,166],"conducted":[75],"different":[79,114],"layers,":[80],"attention":[81],"mechanisms":[82],"case":[84,91],"transformers,":[86],"convolutional":[88],"architectures":[89],"CNNs.":[93],"Besides,":[94],"parameters":[95],"related":[96],"training,":[98],"as":[100,203,205],"learning":[101,258],"rates,":[102],"batch":[103],"sizes,":[104],"optimization":[106,242],"algorithms,":[107],"have":[108,226],"also":[109],"been":[110],"systematically":[111],"tuned.":[112],"evaluated":[117],"against":[118],"accuracy,":[119,160],"precision,":[120,162],"recall,":[121,202],"F1-score.":[124],"Our":[125],"results":[126,235],"show":[127],"that":[128,179],"model,":[132],"accuracy":[134],"from":[135,300],"92.5":[136,153],"93.2,":[138],"F1-scores":[139],"91.5":[141,146],"92.2,":[143,148],"precision":[144,200,231],"recall":[150,164],"values":[151,165],"93.2.":[155],"contrast,":[157],"much":[158],"lower":[159],"F1-scores,":[161],"noticed":[167],"when":[168],"using":[169],"baselines,":[170],"especially":[171,183],"VGG.":[172],"All":[173],"these":[174,286],"findings":[175],"indicate":[176],"fact":[178],"presented":[181],"techniques,":[182],"Multimodal":[185],"Transformer":[187],"models,":[188],"more":[190,269],"robust":[191],"solutions":[192],"for":[193,267],"classification":[194],"tasks":[195],"better":[197,230],"balance":[198],"well":[204],"higher":[207],"overall":[208],"accuracy.":[209],"This":[210,251],"came":[211],"cost":[214],"expense":[217],"computational":[219],"resources:":[220],"CNNs":[221],"less":[223],"resource-intensive":[224],"but":[225],"competitive":[227],"recall.":[233],"underline":[236],"how":[237,255],"algorithm":[238],"selection":[239],"hyperparameter":[241],"play":[243],"crucial":[245],"role":[246],"detection":[249],"tasks.":[250],"shown":[254],"state-of-the-art":[256],"deep":[257],"can":[260],"be":[261,284],"effectively":[262],"combined":[263],"data":[266],"building":[268],"efficient":[272],"systems":[273],"Two":[277],"main":[278],"lines":[279],"future":[281],"work":[282],"would":[283],"improving":[285],"understanding":[289],"their":[290],"applicability":[291],"real":[293],"clinical":[294],"practice":[295],"obtain":[297],"maximum":[298],"benefits":[299],"them.":[301]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}