{"id":"https://openalex.org/W4205158607","doi":"https://doi.org/10.1109/bibm52615.2021.9669429","title":"Stacking Approach for Lung Cancer EGFR Mutation Status Prediction from CT Scans","display_name":"Stacking Approach for Lung Cancer EGFR Mutation Status Prediction from CT Scans","publication_year":2021,"publication_date":"2021-12-09","ids":{"openalex":"https://openalex.org/W4205158607","doi":"https://doi.org/10.1109/bibm52615.2021.9669429"},"language":"en","primary_location":{"id":"doi:10.1109/bibm52615.2021.9669429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5010549237","display_name":"Alexandra Ventura","orcid":null},"institutions":[{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":true,"raw_author_name":"Alexandra Ventura","raw_affiliation_strings":["INESC TEC, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"INESC TEC, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001437567","display_name":"T\u00e2nia Pereira","orcid":"https://orcid.org/0000-0003-1681-2436"},"institutions":[{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Tania Pereira","raw_affiliation_strings":["INESC TEC, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"INESC TEC, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100387002","display_name":"Francisco Silva","orcid":"https://orcid.org/0000-0003-3069-2282"},"institutions":[{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Francisco Silva","raw_affiliation_strings":["INESC TEC, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"INESC TEC, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016364489","display_name":"Cl\u00e1udia Freitas","orcid":"https://orcid.org/0000-0002-7162-414X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Claudia Freitas","raw_affiliation_strings":["CHUSJ, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"CHUSJ, Porto, Portugal","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103099779","display_name":"A. Cunha","orcid":"https://orcid.org/0000-0002-3458-7693"},"institutions":[{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Antonio Cunha","raw_affiliation_strings":["INESC TEC, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"INESC TEC, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024451344","display_name":"H\u00e9lder P. Oliveira","orcid":"https://orcid.org/0000-0002-6193-8540"},"institutions":[{"id":"https://openalex.org/I4210166615","display_name":"INESC TEC","ror":"https://ror.org/05fa8ka61","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210125590","https://openalex.org/I4210166615"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Helder P. Oliveira","raw_affiliation_strings":["INESC TEC, Porto, Portugal"],"affiliations":[{"raw_affiliation_string":"INESC TEC, Porto, Portugal","institution_ids":["https://openalex.org/I4210166615"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5010549237"],"corresponding_institution_ids":["https://openalex.org/I4210166615"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.17781155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3099","last_page":"3105"},"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":0.9998999834060669,"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":0.9998999834060669,"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":0.9962000250816345,"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":0.9804999828338623,"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/lung-cancer","display_name":"Lung cancer","score":0.68492192029953},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.5235680937767029},{"id":"https://openalex.org/keywords/cancer","display_name":"Cancer","score":0.4795536696910858},{"id":"https://openalex.org/keywords/mutation","display_name":"Mutation","score":0.4246309995651245},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.38300153613090515},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.37726953625679016},{"id":"https://openalex.org/keywords/oncology","display_name":"Oncology","score":0.29166093468666077},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.21839642524719238},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.13546597957611084},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.1029973030090332},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06339290738105774},{"id":"https://openalex.org/keywords/nuclear-magnetic-resonance","display_name":"Nuclear magnetic resonance","score":0.05847346782684326}],"concepts":[{"id":"https://openalex.org/C2776256026","wikidata":"https://www.wikidata.org/wiki/Q47912","display_name":"Lung cancer","level":2,"score":0.68492192029953},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.5235680937767029},{"id":"https://openalex.org/C121608353","wikidata":"https://www.wikidata.org/wiki/Q12078","display_name":"Cancer","level":2,"score":0.4795536696910858},{"id":"https://openalex.org/C501734568","wikidata":"https://www.wikidata.org/wiki/Q42918","display_name":"Mutation","level":3,"score":0.4246309995651245},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.38300153613090515},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.37726953625679016},{"id":"https://openalex.org/C143998085","wikidata":"https://www.wikidata.org/wiki/Q162555","display_name":"Oncology","level":1,"score":0.29166093468666077},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.21839642524719238},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.13546597957611084},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.1029973030090332},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06339290738105774},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.05847346782684326},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm52615.2021.9669429","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm52615.2021.9669429","pdf_url":null,"source":{"id":"https://openalex.org/S4363607735","display_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.8899999856948853,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2118004874","https://openalex.org/W2496284264","https://openalex.org/W2755012395","https://openalex.org/W2767128594","https://openalex.org/W2767346095","https://openalex.org/W2789758093","https://openalex.org/W2896246551","https://openalex.org/W2902159658","https://openalex.org/W3009259752","https://openalex.org/W3011110107","https://openalex.org/W3011471823","https://openalex.org/W3040038034","https://openalex.org/W3108583367","https://openalex.org/W3116792204","https://openalex.org/W3147464644","https://openalex.org/W3154846286","https://openalex.org/W3157918261","https://openalex.org/W3192519463","https://openalex.org/W4200231441","https://openalex.org/W6774049588"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W3031052312","https://openalex.org/W4389568370","https://openalex.org/W3032375762","https://openalex.org/W1995515455","https://openalex.org/W2080531066","https://openalex.org/W3108674512","https://openalex.org/W1506200166","https://openalex.org/W1489783725","https://openalex.org/W2148612803"],"abstract_inverted_index":{"Due":[0],"to":[1,64,82,87,128,143,228],"the":[2,20,24,27,32,41,61,66,85,97,116,121,133,138,145,161,173,178,210,226,230,234],"huge":[3],"mortality":[4],"rate":[5],"of":[6,26,35,40,99,120,140,168,184,212],"lung":[7,154],"cancer,":[8],"there":[9],"is":[10,43,60,71,78],"a":[11,79,218],"strong":[12],"need":[13],"for":[14,103,160,188,194,202,221],"developing":[15],"solutions":[16],"that":[17,51],"help":[18],"with":[19,92,181],"early":[21],"diagnosis":[22],"and":[23,74,118,198],"definition":[25],"most":[28],"appropriate":[29],"treatment.":[30],"In":[31],"particular":[33],"case":[34],"target":[36],"therapy,":[37],"effective":[38],"genotyping":[39],"tumor":[42],"fundamental":[44],"since":[45],"this":[46,222],"treatment":[47],"uses":[48],"targeted":[49],"drugs":[50],"can":[52],"induce":[53],"death":[54],"in":[55,132,153],"cancer":[56],"cells.":[57],"The":[58,156,205],"biopsy":[59],"traditional":[62],"method":[63],"assess":[65],"genotype":[67],"information":[68],"but":[69],"it":[70],"extremely":[72],"invasive":[73],"painful.":[75],"Medical":[76],"imaging":[77,89],"valuable":[80,112],"alternative":[81],"biopsies,":[83],"considering":[84],"potential":[86],"extract":[88],"features":[90],"correlated":[91],"specific":[93],"genomic":[94],"alterations.":[95],"Regarding":[96],"limitations":[98],"single":[100,179,214,235],"model":[101,215],"approaches":[102],"gene":[104],"mutation":[105,151],"status":[106,152],"predictions,":[107],"ensemble":[108,141,163,174,227],"strategies":[109],"might":[110,216],"bring":[111],"benefits":[113],"by":[114,136],"combining":[115],"strengths":[117],"weaknesses":[119],"aggregated":[122],"methods.":[123],"This":[124],"preliminary":[125],"work":[126],"aims":[127],"provide":[129],"further":[130],"advances":[131],"radiogenomics":[134],"field":[135],"studying":[137],"use":[139],"methods":[142],"predict":[144],"Epidermal":[146],"Growth":[147],"Factor":[148],"Receptor":[149],"(EGFR)":[150],"cancer.":[155],"best":[157],"result":[158],"obtained":[159],"proposed":[162],"approach":[164],"was":[165],"an":[166],"AUC":[167,182],"0.706":[169],"(&#x00B1;":[170,186,192,200],"0.122).":[171],"However,":[172],"did":[175],"not":[176],"outperform":[177],"models":[180],"values":[183],"0.712":[185,199],"0.119)":[187,193],"Logistic":[189],"Regression,":[190],"0.711":[191],"Support":[195],"Vector":[196],"Machine":[197],"0.120)":[201],"Elastic":[203],"Net.":[204],"high":[206],"correlation":[207],"found":[208],"on":[209],"decisions":[211],"each":[213],"be":[217],"plausible":[219],"explanation":[220],"behavior,":[223],"which":[224],"caused":[225],"misclassify":[229],"same":[231],"examples":[232],"as":[233],"models.":[236]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
