{"id":"https://openalex.org/W4415420309","doi":"https://doi.org/10.1186/s12880-025-01903-x","title":"A robust and data-efficient deep learning model for cardiac assessment without segmentation","display_name":"A robust and data-efficient deep learning model for cardiac assessment without segmentation","publication_year":2025,"publication_date":"2025-10-22","ids":{"openalex":"https://openalex.org/W4415420309","doi":"https://doi.org/10.1186/s12880-025-01903-x","pmid":"https://pubmed.ncbi.nlm.nih.gov/41126099"},"language":"en","primary_location":{"id":"doi:10.1186/s12880-025-01903-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-025-01903-x","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-025-01903-x","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-025-01903-x","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5114423479","display_name":"Conor M. Artman","orcid":null},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Conor M. Artman","raw_affiliation_strings":["AI Research Group, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, 94550, USA. artman1@llnl.gov","AI Research Group, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, 94550, USA"],"affiliations":[{"raw_affiliation_string":"AI Research Group, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, 94550, USA. artman1@llnl.gov","institution_ids":[]},{"raw_affiliation_string":"AI Research Group, Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, CA, 94550, USA","institution_ids":["https://openalex.org/I1282311441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056639842","display_name":"Ricardo Henao","orcid":"https://orcid.org/0000-0003-4980-845X"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ricardo Henao","raw_affiliation_strings":["Department of Biostatistics & Bioinformatics, Duke University, 2424 Erwin Road Suite 1104, Durham, 27705, NC, USA. ricardo.henao@duke.edu","Department of Biostatistics & Bioinformatics, Duke University, 2424 Erwin Road Suite 1104, Durham, 27705, NC, USA"],"affiliations":[{"raw_affiliation_string":"Department of Biostatistics & Bioinformatics, Duke University, 2424 Erwin Road Suite 1104, Durham, 27705, NC, USA. ricardo.henao@duke.edu","institution_ids":[]},{"raw_affiliation_string":"Department of Biostatistics & Bioinformatics, Duke University, 2424 Erwin Road Suite 1104, Durham, 27705, NC, USA","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5056639842","https://openalex.org/A5114423479"],"corresponding_institution_ids":["https://openalex.org/I1282311441","https://openalex.org/I170897317"],"apc_list":{"value":1690,"currency":"GBP","value_usd":2072},"apc_paid":{"value":1690,"currency":"GBP","value_usd":2072},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.45430872,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"25","issue":"1","first_page":"423","last_page":"423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9969000220298767,"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/T11021","display_name":"ECG Monitoring and Analysis","score":0.9969000220298767,"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/T10821","display_name":"Cardiovascular Function and Risk Factors","score":0.9950000047683716,"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/T10372","display_name":"Cardiac Imaging and Diagnostics","score":0.9940000176429749,"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/segmentation","display_name":"Segmentation","score":0.7626000046730042},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.75},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7494999766349792},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7114999890327454},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5963000059127808},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4896000027656555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4147999882698059},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41100001335144043}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896999716758728},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7626000046730042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7560999989509583},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.75},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7494999766349792},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7114999890327454},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5963000059127808},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4896000027656555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41100001335144043},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.3758000135421753},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.37450000643730164},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3472999930381775},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31470000743865967},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.31060001254081726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3046000003814697},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.28290000557899475},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.2797999978065491},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.27489998936653137},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.2540999948978424}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1186/s12880-025-01903-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-025-01903-x","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-025-01903-x","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},{"id":"pmid:41126099","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41126099","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":"BMC medical imaging","raw_type":null},{"id":"pmh:oai:doaj.org/article:feb22f03a05241ee82813c9ad854369d","is_oa":true,"landing_page_url":"https://doaj.org/article/feb22f03a05241ee82813c9ad854369d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Medical Imaging, Vol 25, Iss 1, Pp 1-16 (2025)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:11349810","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/12541996","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1186/s12880-025-01903-x","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s12880-025-01903-x","pdf_url":"https://bmcmedimaging.biomedcentral.com/counter/pdf/10.1186/s12880-025-01903-x","source":{"id":"https://openalex.org/S6505649","display_name":"BMC Medical Imaging","issn_l":"1471-2342","issn":["1471-2342"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Medical Imaging","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4677375346","display_name":null,"funder_award_id":"HL079896","funder_id":"https://openalex.org/F4320337338","funder_display_name":"National Heart, Lung, and Blood Institute"}],"funders":[{"id":"https://openalex.org/F4320337338","display_name":"National Heart, Lung, and Blood Institute","ror":"https://ror.org/012pb6c26"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4415420309.pdf"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1129605249","https://openalex.org/W1753280301","https://openalex.org/W1984973071","https://openalex.org/W1998363540","https://openalex.org/W2013364878","https://openalex.org/W2025001482","https://openalex.org/W2035920013","https://openalex.org/W2088378134","https://openalex.org/W2119249988","https://openalex.org/W2144643813","https://openalex.org/W2161254570","https://openalex.org/W2190898938","https://openalex.org/W2194775991","https://openalex.org/W2280684980","https://openalex.org/W2313077061","https://openalex.org/W2596978933","https://openalex.org/W2620296437","https://openalex.org/W2754901918","https://openalex.org/W2769309750","https://openalex.org/W2788388592","https://openalex.org/W2885500297","https://openalex.org/W2891975710","https://openalex.org/W2901383458","https://openalex.org/W2915232829","https://openalex.org/W2919020930","https://openalex.org/W2919949127","https://openalex.org/W2963155035","https://openalex.org/W2971649496","https://openalex.org/W3007935259","https://openalex.org/W3011912756","https://openalex.org/W3013692475","https://openalex.org/W3014537148","https://openalex.org/W3014974815","https://openalex.org/W3112701542","https://openalex.org/W4249896096","https://openalex.org/W4283783398","https://openalex.org/W4289085709","https://openalex.org/W4319444024","https://openalex.org/W4321766254","https://openalex.org/W4376598121","https://openalex.org/W4385552881","https://openalex.org/W4386265006","https://openalex.org/W4391093797","https://openalex.org/W4398188123","https://openalex.org/W4401389291","https://openalex.org/W4408278187","https://openalex.org/W4408678691","https://openalex.org/W4410343507"],"related_works":[],"abstract_inverted_index":{"Video-based":[0],"deep":[1],"learning":[2],"(DL)":[3],"algorithms":[4,22],"often":[5],"rely":[6],"on":[7,156],"segmentation":[8,68,74,123],"models":[9],"to":[10,34,57,89,102,133,145,154],"detect":[11],"clinically":[12],"important":[13],"features":[14],"in":[15],"transthoracic":[16],"echocardiograms":[17],"(TTEs).":[18],"While":[19],"effective,":[20],"these":[21,41,58],"can":[23,108],"be":[24,32,109],"too":[25],"data":[26,36,60],"hungry":[27],"for":[28,111,121],"practice":[29],"and":[30,78],"may":[31],"sensitive":[33],"common":[35,59],"quality":[37,61],"issues.":[38],"To":[39],"overcome":[40],"concerns,":[42],"we":[43,76],"present":[44],"a":[45,73,104,122],"data-efficient":[46],"DL":[47],"algorithm,":[48],"Scaled":[49],"Gumbel":[50],"Softmax":[51],"(SGS)":[52],"EchoNet,":[53],"that":[54,98,107,115,139],"is":[55],"robust":[56],"issues":[62],"and,":[63],"importantly,":[64],"requires":[65],"no":[66],"ventricular":[67],"model.":[69],"In":[70],"lieu":[71],"of":[72,82,129,148],"model,":[75],"decompose":[77],"transform":[79],"the":[80,95,119,127,130,146,149],"output":[81],"an":[83,157],"R(2":[84],"+":[85],"1)D":[86],"convolutional":[87],"encoder":[88],"estimate":[90],"frame-level":[91],"weights":[92],"associated":[93],"with":[94],"cardiac":[96],"cycle,":[97],"are":[99],"then":[100],"used":[101,110],"obtain":[103],"video":[105],"representation":[106],"estimation.":[112],"We":[113,137],"find":[114],"our":[116,140],"transformation":[117],"obviates":[118],"need":[120],"model":[124,132,141],"while":[125,151],"improving":[126],"ability":[128],"predictive":[131],"handle":[134],"noisy":[135],"inputs.":[136],"show":[138],"achieves":[142],"comparable":[143],"performance":[144],"state":[147],"art,":[150],"demonstrating":[152],"robustness":[153],"noise":[155],"independent":[158],"(external)":[159],"validation":[160],"set.":[161],"Not":[162],"applicable.":[163]},"counts_by_year":[],"updated_date":"2026-03-25T14:56:36.534964","created_date":"2025-10-24T00:00:00"}