{"id":"https://openalex.org/W4295514622","doi":"https://doi.org/10.1109/embc48229.2022.9871257","title":"A Comparative Study on the Potential of Unsupervised Deep Learning-based Feature Selection in Radiomics","display_name":"A Comparative Study on the Potential of Unsupervised Deep Learning-based Feature Selection in Radiomics","publication_year":2022,"publication_date":"2022-07-11","ids":{"openalex":"https://openalex.org/W4295514622","doi":"https://doi.org/10.1109/embc48229.2022.9871257","pmid":"https://pubmed.ncbi.nlm.nih.gov/36085959"},"language":"en","primary_location":{"id":"doi:10.1109/embc48229.2022.9871257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9871257","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","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":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5018338067","display_name":"Tobias Haueise","orcid":"https://orcid.org/0000-0002-1462-7539"},"institutions":[{"id":"https://openalex.org/I4387152912","display_name":"Institute of Diabetes Research","ror":"https://ror.org/0278hns33","country_code":null,"type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I3018134672","https://openalex.org/I4387152912"]},{"id":"https://openalex.org/I4210160326","display_name":"German Center for Diabetes Research","ror":"https://ror.org/04qq88z54","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210160326","https://openalex.org/I4405256427"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tobias Haueise","raw_affiliation_strings":["University Hospital Tuebingen,Section on Experimental Radiology,Tuebingen,Germany","Section on Experimental Radiology, University Hospital Tuebingen, Tuebingen, Germany","Institute of Diabetes Research and Metabolic Diseases at Helmholtz Munich, Tuebingen, Germany"],"affiliations":[{"raw_affiliation_string":"University Hospital Tuebingen,Section on Experimental Radiology,Tuebingen,Germany","institution_ids":[]},{"raw_affiliation_string":"Section on Experimental Radiology, University Hospital Tuebingen, Tuebingen, Germany","institution_ids":[]},{"raw_affiliation_string":"Institute of Diabetes Research and Metabolic Diseases at Helmholtz Munich, Tuebingen, Germany","institution_ids":["https://openalex.org/I4210160326","https://openalex.org/I4387152912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059737056","display_name":"Annika Liebgott","orcid":"https://orcid.org/0000-0001-7623-9534"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Annika Liebgott","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany","Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany","institution_ids":["https://openalex.org/I100066346"]},{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101717968","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-8322-117X"},"institutions":[{"id":"https://openalex.org/I100066346","display_name":"University of Stuttgart","ror":"https://ror.org/04vnq7t77","country_code":"DE","type":"education","lineage":["https://openalex.org/I100066346"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany","Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany"],"affiliations":[{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany","institution_ids":["https://openalex.org/I100066346"]},{"raw_affiliation_string":"Institute of Signal Processing and System Theory, University of Stuttgart, Stuttgart, Germany","institution_ids":["https://openalex.org/I100066346"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018338067"],"corresponding_institution_ids":["https://openalex.org/I4210160326","https://openalex.org/I4387152912"],"apc_list":null,"apc_paid":null,"fwci":1.3387,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.85541087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"2022","issue":null,"first_page":"541","last_page":"544"},"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/T10862","display_name":"AI in cancer detection","score":0.9908999800682068,"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/T12386","display_name":"Advanced X-ray and CT Imaging","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.8657513856887817},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8096598386764526},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.7939910292625427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7303803563117981},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6894489526748657},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6073850393295288},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5808998346328735},{"id":"https://openalex.org/keywords/radiomics","display_name":"Radiomics","score":0.5191985368728638},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5154284238815308},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4896993935108185},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.46725863218307495},{"id":"https://openalex.org/keywords/minimum-redundancy-feature-selection","display_name":"Minimum redundancy feature selection","score":0.45830419659614563},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4371475875377655},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4244646430015564},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.41550832986831665},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.22855141758918762},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08912447094917297}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8657513856887817},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8096598386764526},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7939910292625427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7303803563117981},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6894489526748657},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6073850393295288},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5808998346328735},{"id":"https://openalex.org/C2778559731","wikidata":"https://www.wikidata.org/wiki/Q23808793","display_name":"Radiomics","level":2,"score":0.5191985368728638},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5154284238815308},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4896993935108185},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.46725863218307495},{"id":"https://openalex.org/C16811321","wikidata":"https://www.wikidata.org/wiki/Q17138905","display_name":"Minimum redundancy feature selection","level":3,"score":0.45830419659614563},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4371475875377655},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4244646430015564},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.41550832986831665},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.22855141758918762},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08912447094917297},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000077321","descriptor_name":"Deep Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018401","descriptor_name":"Sample Size","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018401","descriptor_name":"Sample Size","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D018401","descriptor_name":"Sample Size","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1109/embc48229.2022.9871257","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc48229.2022.9871257","pdf_url":null,"source":{"id":"https://openalex.org/S4363607706","display_name":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","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":"2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:36085959","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36085959","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null},{"id":"pmh:oai:opus-zb.helmholtz-muenchen.de:67029","is_oa":false,"landing_page_url":"https://push-zb.helmholtz-muenchen.de/frontdoor.php?source_opus=67029","pdf_url":null,"source":{"id":"https://openalex.org/S4377196115","display_name":"Site cant be reached","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In:. 2022. 541-544 ( ; 2022)","raw_type":"Text"},{"id":"pmh:oai:push-zb.helmholtz-munich.de:67029","is_oa":false,"landing_page_url":"https://push-zb.helmholtz-munich.de/frontdoor.php?source_opus=67029","pdf_url":null,"source":{"id":"https://openalex.org/S7407055352","display_name":"PuSH - Publication Server of Helmholtz Zentrum M\u00fcnchen","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"In:. 2022. 541-544 ( ; 2022)","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1545302199","https://openalex.org/W1964754236","https://openalex.org/W2009501510","https://openalex.org/W2027913322","https://openalex.org/W2101234009","https://openalex.org/W2104862701","https://openalex.org/W2149620660","https://openalex.org/W2170585273","https://openalex.org/W2174661749","https://openalex.org/W2187089797","https://openalex.org/W2548228487","https://openalex.org/W2606926876","https://openalex.org/W2767128594","https://openalex.org/W2787225914","https://openalex.org/W2807086064","https://openalex.org/W2903659352","https://openalex.org/W2915126261","https://openalex.org/W2952621348","https://openalex.org/W2960473173","https://openalex.org/W2990742598","https://openalex.org/W2996673142","https://openalex.org/W3009418934","https://openalex.org/W3025036301","https://openalex.org/W3080141629","https://openalex.org/W3105251098","https://openalex.org/W3113707989","https://openalex.org/W3132467135","https://openalex.org/W3169811183","https://openalex.org/W3200608663","https://openalex.org/W6652451885","https://openalex.org/W6675354045","https://openalex.org/W6681822384","https://openalex.org/W6685450415","https://openalex.org/W6758532572","https://openalex.org/W6787906751"],"related_works":["https://openalex.org/W3174759195","https://openalex.org/W3167013339","https://openalex.org/W4287121366","https://openalex.org/W60493759","https://openalex.org/W4386437125","https://openalex.org/W4308619659","https://openalex.org/W3213069564","https://openalex.org/W2997229301","https://openalex.org/W2785325870","https://openalex.org/W2794802664"],"abstract_inverted_index":{"In":[0],"Radiomics,":[1],"deep":[2,72,102],"learning-based":[3,73,103],"systems":[4,20],"for":[5,75,116,138,147,171],"medical":[6],"image":[7],"analysis":[8],"play":[9],"an":[10,58],"increasing":[11],"role.":[12],"However,":[13],"due":[14],"to":[15,42,107,112,131],"the":[16,53,129,136,156],"better":[17],"explainability,":[18],"feature-based":[19],"are":[21,82],"still":[22],"preferred,":[23],"especially":[24,115],"by":[25],"physicians.":[26],"Often,":[27],"high-dimensional":[28],"data":[29,91],"and":[30,49,87,128,173],"low":[31],"sample":[32,96],"size":[33],"pose":[34],"different":[35,95],"challenges":[36],"(e.g.":[37],"increased":[38],"risk":[39],"of":[40,61,125,145,158,164],"overfitting)":[41],"machine":[43],"learning":[44],"systems.":[45],"By":[46],"removing":[47],"irrelevant":[48],"redundant":[50],"features":[51,127,159],"from":[52],"data,":[54],"feature":[55,76,104,118,149],"selection":[56,105,150],"is":[57,68,141,160,168],"effective":[59],"way":[60],"pre-processing.":[62],"The":[63,123,162],"research":[64],"in":[65,93,153],"this":[66],"study":[67],"focused":[69],"on":[70,89],"unsupervised":[71,148],"methods":[74],"selection.":[77],"Five":[78],"recently":[79],"proposed":[80],"algorithms":[81],"compared":[83,111],"regarding":[84],"their":[85,133],"applicability":[86],"efficiency":[88],"seven":[90],"sets":[92],"three":[94],"applications.":[97],"It":[98],"was":[99],"found":[100],"that":[101],"leads":[106],"improved":[108],"classification":[109],"results":[110],"conventional":[113],"methods,":[114],"small":[117],"subsets.":[119],"Clinical":[120],"Relevance":[121],"-":[122],"exploration":[124],"distinctive":[126],"ability":[130],"rank":[132],"importance":[134],"without":[135],"need":[137],"outcome":[139],"information":[140],"a":[142],"potential":[143,166],"field":[144],"application":[146],"methods.":[151],"Especially":[152],"multiparametric":[154],"radiology,":[155],"number":[157],"increasing.":[161],"identification":[163],"new":[165],"biomarkers":[167],"important":[169],"both":[170],"treatment":[172],"prevention.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-02T08:37:19.008085","created_date":"2025-10-10T00:00:00"}