{"id":"https://openalex.org/W4417250544","doi":"https://doi.org/10.1109/bibe66822.2025.00047","title":"Comparative Assessment of Uncertainty-Aware Deep Learning Methods for Atherosclerosis Risk Stratification from Carotid Ultrasound Imaging","display_name":"Comparative Assessment of Uncertainty-Aware Deep Learning Methods for Atherosclerosis Risk Stratification from Carotid Ultrasound Imaging","publication_year":2025,"publication_date":"2025-11-06","ids":{"openalex":"https://openalex.org/W4417250544","doi":"https://doi.org/10.1109/bibe66822.2025.00047"},"language":null,"primary_location":{"id":"doi:10.1109/bibe66822.2025.00047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","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/A5120775973","display_name":"Kalliopi Sarafi","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Kalliopi Sarafi","raw_affiliation_strings":["School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021038994","display_name":"Theofanis Ganitidis","orcid":"https://orcid.org/0009-0006-7794-9793"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Theofanis Ganitidis","raw_affiliation_strings":["School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016849904","display_name":"\u039c\u03b1\u03c1\u03af\u03b1 \u0391\u03b8\u03b1\u03bd\u03b1\u03c3\u03af\u03bf\u03c5","orcid":"https://orcid.org/0000-0003-1575-9100"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Maria Athanasiou","raw_affiliation_strings":["School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082313849","display_name":"Konstantina S. Nikita","orcid":"https://orcid.org/0000-0001-8255-4354"},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Konstantina S. Nikita","raw_affiliation_strings":["School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering National Technical University of Athens,Athens,Greece","institution_ids":["https://openalex.org/I174458059"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5120775973"],"corresponding_institution_ids":["https://openalex.org/I174458059"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.58565115,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"230","last_page":"235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":0.20909999310970306,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/T10924","display_name":"Cardiovascular Health and Disease Prevention","score":0.20909999310970306,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/T10816","display_name":"Cerebrovascular and Carotid Artery Diseases","score":0.13619999587535858,"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/T10727","display_name":"Ultrasound Imaging and Elastography","score":0.10610000044107437,"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/deep-learning","display_name":"Deep learning","score":0.6647999882698059},{"id":"https://openalex.org/keywords/risk-stratification","display_name":"Risk stratification","score":0.5867999792098999},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5213000178337097},{"id":"https://openalex.org/keywords/risk-assessment","display_name":"Risk assessment","score":0.5152000188827515},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.41429999470710754},{"id":"https://openalex.org/keywords/ultrasound-imaging","display_name":"Ultrasound imaging","score":0.4113999903202057},{"id":"https://openalex.org/keywords/clinical-practice","display_name":"Clinical Practice","score":0.41019999980926514},{"id":"https://openalex.org/keywords/ultrasound","display_name":"Ultrasound","score":0.3862999975681305},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.3765000104904175}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6647999882698059},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6098999977111816},{"id":"https://openalex.org/C3020404979","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk stratification","level":2,"score":0.5867999792098999},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.5299000144004822},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5213000178337097},{"id":"https://openalex.org/C12174686","wikidata":"https://www.wikidata.org/wiki/Q1058438","display_name":"Risk assessment","level":2,"score":0.5152000188827515},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47609999775886536},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.41429999470710754},{"id":"https://openalex.org/C2986892559","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Ultrasound imaging","level":3,"score":0.4113999903202057},{"id":"https://openalex.org/C2779974597","wikidata":"https://www.wikidata.org/wiki/Q28448986","display_name":"Clinical Practice","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C143753070","wikidata":"https://www.wikidata.org/wiki/Q162564","display_name":"Ultrasound","level":2,"score":0.3862999975681305},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3765000104904175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3752000033855438},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37290000915527344},{"id":"https://openalex.org/C31601959","wikidata":"https://www.wikidata.org/wiki/Q931309","display_name":"Medical imaging","level":2,"score":0.3635999858379364},{"id":"https://openalex.org/C2992165143","wikidata":"https://www.wikidata.org/wiki/Q234904","display_name":"Medical ultrasound","level":3,"score":0.3425999879837036},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.34139999747276306},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C2776210653","wikidata":"https://www.wikidata.org/wiki/Q20707753","display_name":"Atherosclerosis Risk in Communities","level":3,"score":0.30079999566078186},{"id":"https://openalex.org/C2987047532","wikidata":"https://www.wikidata.org/wiki/Q214275","display_name":"Carotid arteries","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C117765406","wikidata":"https://www.wikidata.org/wiki/Q5362437","display_name":"Generalization error","level":3,"score":0.2833999991416931},{"id":"https://openalex.org/C2989179672","wikidata":"https://www.wikidata.org/wiki/Q6806500","display_name":"Clinical decision making","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2759999930858612},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C144587487","wikidata":"https://www.wikidata.org/wiki/Q1369234","display_name":"Systemic risk","level":3,"score":0.26589998602867126},{"id":"https://openalex.org/C544519230","wikidata":"https://www.wikidata.org/wiki/Q32566","display_name":"Computed tomography","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C137209882","wikidata":"https://www.wikidata.org/wiki/Q1403517","display_name":"Measurement uncertainty","level":2,"score":0.25850000977516174}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibe66822.2025.00047","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibe66822.2025.00047","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 25th International Conference on Bioinformatics and Bioengineering (BIBE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2592929672","https://openalex.org/W2951965145","https://openalex.org/W2991372685","https://openalex.org/W3019335011","https://openalex.org/W3020285846","https://openalex.org/W3041936152","https://openalex.org/W3158112749","https://openalex.org/W4200023209","https://openalex.org/W4221129115","https://openalex.org/W4282942659","https://openalex.org/W4394938905","https://openalex.org/W4396796802","https://openalex.org/W4405917215"],"related_works":[],"abstract_inverted_index":{"Carotid":[0],"atherosclerosis":[1],"represents":[2],"a":[3],"major":[4],"risk":[5,12,59],"factor":[6],"for":[7,14,70,78],"ischemic":[8],"stroke,":[9],"requiring":[10],"accurate":[11],"stratification":[13],"effective":[15],"clinical":[16,37,149],"intervention.":[17],"While":[18],"deep":[19],"learning":[20],"models":[21],"demonstrate":[22,97],"excellent":[23],"performance":[24],"in":[25,36,57,113,148],"medical":[26],"image":[27],"analysis,":[28],"their":[29],"lack":[30],"of":[31,44,136,144],"uncertainty":[32,46,119,128,145],"quantification":[33],"limits":[34],"deployment":[35],"environments.":[38],"This":[39],"study":[40],"investigates":[41],"the":[42,67,88,133,141],"use":[43],"two":[45,73],"estimation":[47],"techniques,":[48],"Monte":[49],"Carlo":[50],"Dropout":[51],"(MCD)":[52],"and":[53,72,76,84,92,103,139],"Deep":[54],"Ensembles":[55],"(DE),":[56],"cardiovascular":[58],"prediction":[60],"from":[61],"B-mode":[62],"carotid":[63],"ultrasound":[64],"images.":[65],"Using":[66],"CUBS":[68],"dataset":[69],"training":[71],"datasets":[74],"(ATTIKON":[75],"BUSI)":[77],"external":[79],"evaluation":[80],"under":[81],"distributional":[82],"shift":[83],"out-of-distribution":[85],"(OOD)":[86],"conditions,":[87],"model's":[89],"performance,":[90],"calibration,":[91],"robustness":[93],"are":[94],"assessed.":[95],"Results":[96],"that":[98],"MCD":[99],"provides":[100],"superior":[101],"generalization":[102],"OOD":[104],"detection":[105],"capabilities":[106],"(<tex":[107],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[108],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\text{AUC}=0.9589$</tex>),":[109],"while":[110],"DE":[111],"excels":[112],"graceful":[114],"degradation":[115],"through":[116],"rejecting":[117],"high":[118],"samples,":[120],"achieving":[121],"16.49":[122],"%":[123],"accuracy":[124],"improvement":[125],"on":[126],"low":[127],"samples.":[129],"These":[130],"findings":[131],"highlight":[132],"complementary":[134],"strengths":[135],"both":[137],"methods":[138],"underscore":[140],"critical":[142],"importance":[143],"aware":[146],"AI":[147],"decision":[150],"support":[151],"systems.":[152]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-11T00:00:00"}
