{"id":"https://openalex.org/W7222955366","doi":"https://doi.org/10.64898/2026.10.17.26365795","title":"Teaching an ECG model where to look does not make it more robust to missing leads: a pre-registered comparison of guideline-based attention guidance with random lead masking","display_name":"Teaching an ECG model where to look does not make it more robust to missing leads: a pre-registered comparison of guideline-based attention guidance with random lead masking","publication_year":2026,"publication_date":"2026-10-19","ids":{"openalex":"https://openalex.org/W7222955366","doi":"https://doi.org/10.64898/2026.10.17.26365795"},"language":"en","primary_location":{"id":"doi:10.64898/2026.10.17.26365795","doi":"https://doi.org/10.64898/2026.10.17.26365795","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.17.26365795","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2026/10/19/2026.10.17.26365795.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.medrxiv.org/content/medrxiv/early/2026/10/19/2026.10.17.26365795.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5158927831","display_name":"Mohamed Nour Bou Ali","orcid":"https://orcid.org/0009-0002-1069-1805","observed_orcids":["https://orcid.org/0009-0002-1069-1805"]},"institutions":[{"id":"https://openalex.org/I166928557","display_name":"University of Monastir","ror":"https://ror.org/00nhtcg76","country_code":"TN","type":"education","lineage":["https://openalex.org/I166928557"]}],"countries":["TN"],"is_corresponding":true,"raw_author_name":"Mohamed Nour Bou Ali","raw_affiliation_strings":["Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia"],"raw_orcid":"https://orcid.org/0009-0002-1069-1805","affiliations":[{"raw_affiliation_string":"Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia","institution_ids":["https://openalex.org/I166928557"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5159057415","display_name":"Mohamed Mahmoud","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I166928557","display_name":"University of Monastir","ror":"https://ror.org/00nhtcg76","country_code":"TN","type":"education","lineage":["https://openalex.org/I166928557"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Mohamed Mahmoud","raw_affiliation_strings":["Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Medicine of Monastir, University of Monastir, Monastir, Tunisia","institution_ids":["https://openalex.org/I166928557"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5158927831"],"corresponding_institution_ids":["https://openalex.org/I166928557"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9976000189781189,"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":0.9976000189781189,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.0012000000569969416,"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/T10217","display_name":"Cardiac electrophysiology and arrhythmias","score":0.00019999999494757503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/12-lead-electrocardiogram","display_name":"12-lead ECG","score":0.9359999895095825},{"id":"https://openalex.org/keywords/attentional-guidance","display_name":"attention guidance","score":0.7760000228881836},{"id":"https://openalex.org/keywords/clinical-guidelines","display_name":"clinical guidelines","score":0.6650000214576721},{"id":"https://openalex.org/keywords/ecg-classification","display_name":"ECG classification","score":0.5590000152587891},{"id":"https://openalex.org/keywords/bundle-branch-block","display_name":"bundle branch block","score":0.6890000104904175},{"id":"https://openalex.org/keywords/atrial-fibrillation","display_name":"atrial fibrillation","score":0.9580000042915344},{"id":"https://openalex.org/keywords/first-degree-av-block","display_name":"first-degree AV block","score":0.8980000019073486},{"id":"https://openalex.org/keywords/robustness","display_name":"robustness","score":0.4490000009536743},{"id":"https://openalex.org/keywords/ptb-xl","display_name":"PTB-XL","score":0.7080000042915344},{"id":"https://openalex.org/keywords/calibration","display_name":"calibration","score":0.3779999911785126},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.4090000092983246},{"id":"https://openalex.org/keywords/external-validation","display_name":"external validation","score":0.5090000033378601},{"id":"https://openalex.org/keywords/bootstrap-confidence-intervals","display_name":"bootstrap confidence intervals","score":0.5},{"id":"https://openalex.org/keywords/non-inferiority","display_name":"non-inferiority","score":0.597000002861023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5468000173568726},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5073000192642212},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.4993000030517578},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4049000144004822},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.40290001034736633},{"id":"https://openalex.org/C44249647","wikidata":"https://www.wikidata.org/wiki/Q208498","display_name":"Confidence interval","level":2,"score":0.39160001277923584},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37560001015663147},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C2777093003","wikidata":"https://www.wikidata.org/wiki/Q6508345","display_name":"Lead (geology)","level":2,"score":0.3601999878883362},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3589000105857849},{"id":"https://openalex.org/C73782692","wikidata":"https://www.wikidata.org/wiki/Q196372","display_name":"Random error","level":2,"score":0.3490999937057495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3411000072956085},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C111773187","wikidata":"https://www.wikidata.org/wiki/Q1969239","display_name":"QRS complex","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C2777473070","wikidata":"https://www.wikidata.org/wiki/Q2143688","display_name":"Left bundle branch block","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.27970001101493835},{"id":"https://openalex.org/C3018023364","wikidata":"https://www.wikidata.org/wiki/Q425265","display_name":"Significant difference","level":2,"score":0.25929999351501465}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.64898/2026.10.17.26365795","doi":"https://doi.org/10.64898/2026.10.17.26365795","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.17.26365795","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2026/10/19/2026.10.17.26365795.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.64898/2026.10.17.26365795","doi":"https://doi.org/10.64898/2026.10.17.26365795","is_oa":true,"landing_page_url":"https://doi.org/10.64898/2026.10.17.26365795","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2026/10/19/2026.10.17.26365795.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.6240000128746033,"id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7222955366.pdf","grobid_xml":"https://content.openalex.org/works/W7222955366.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1525161423","https://openalex.org/W2037698344","https://openalex.org/W2121044470","https://openalex.org/W2125640901","https://openalex.org/W2126728600","https://openalex.org/W2159738997","https://openalex.org/W2194775991","https://openalex.org/W2328176404","https://openalex.org/W2431622239","https://openalex.org/W2595017202","https://openalex.org/W2610184543","https://openalex.org/W2750333171","https://openalex.org/W2779812635","https://openalex.org/W2902644322","https://openalex.org/W2934842096","https://openalex.org/W2945976633","https://openalex.org/W2965520043","https://openalex.org/W2968210605","https://openalex.org/W2987985090","https://openalex.org/W2996480032","https://openalex.org/W3015226328","https://openalex.org/W3016970897","https://openalex.org/W3027572331","https://openalex.org/W3127657277","https://openalex.org/W3195084370","https://openalex.org/W3208277681","https://openalex.org/W3209901185","https://openalex.org/W4206135956","https://openalex.org/W4220906358","https://openalex.org/W4237155685","https://openalex.org/W4238277289","https://openalex.org/W4367665547","https://openalex.org/W4389166035","https://openalex.org/W4393486865","https://openalex.org/W4394857110","https://openalex.org/W4396670015","https://openalex.org/W4407683233","https://openalex.org/W4409469120","https://openalex.org/W4416035031","https://openalex.org/W6959434663","https://openalex.org/W7134913262","https://openalex.org/W7140405555"],"related_works":["https://openalex.org/W4221153045","https://openalex.org/W7223020962","https://openalex.org/W4313019775","https://openalex.org/W7164950961","https://openalex.org/W7172553854","https://openalex.org/W7143474339","https://openalex.org/W4402712149","https://openalex.org/W7162450330","https://openalex.org/W4285044750","https://openalex.org/W4401576741"],"abstract_inverted_index":{"Abstract":[0],"Background":[1],"Real-world":[2],"12-lead":[3],"electrocardiograms":[4],"(ECGs)":[5],"often":[6],"have":[7],"missing":[8,317],"or":[9,26],"corrupted":[10],"leads.":[11],"A":[12],"deep-learning":[13],"classifier":[14,314],"can":[15],"be":[16,338],"prepared":[17],"for":[18,31,43,257],"this":[19,47],"by":[20,27,33,228],"random":[21,77],"lead":[22,215,307],"masking":[23,52,79,81,308],"during":[24],"training,":[25],"injecting":[28],"clinical":[29,325],"knowledge,":[30],"example":[32],"pulling":[34,86],"its":[35,252],"attention":[36,69,87,96,240,323,335],"towards":[37,88],"the":[38,71,181,185,219,242],"leads":[39,223,271,283,292],"that":[40],"guidelines":[41],"use":[42],"each":[44],"diagnosis.":[45],"Whether":[46],"knowledge":[48,321],"adds":[49,328],"robustness":[50,330],"beyond":[51],"is":[53],"unknown.":[54],"Methods":[55],"Pre-registered":[56],"comparison":[57],"of":[58,221,342],"three":[59,282],"arms":[60],"sharing":[61],"one":[62,213,280],"network":[63],"(per-lead":[64],"1D-ResNet":[65],"encoder":[66],"and":[67,118,138,143,146,196,218,244,276,331],"per-diagnosis":[68],"over":[70,133,147],"12":[72],"leads):":[73],"standard":[74],"training":[75],"(M0);":[76],"whole-lead":[78],"(M1);":[80],"plus":[82],"a":[83,89,155],"Kullback-Leibler":[84],"penalty":[85],"fixed":[90],"guideline-derived":[91],"key-lead":[92],"map":[93,243],"(M2,":[94],"guideline-based":[95],"guidance).":[97],"Six":[98],"diagnoses;":[99],"five":[100],"seeds":[101],"per":[102],"arm.":[103],"Development":[104],"on":[105,112,119,248],"PTB-XL":[106,113],"(21,799":[107],"ECGs);":[108],"single":[109],"sealed":[110],"evaluation":[111],"fold":[114],"10":[115,237],"(2,198":[116],"ECGs)":[117],"CODE-15%":[120,294],"(233,204":[121],"exams,":[122],"external":[123],"validation).":[124],"Primary":[125],"endpoint:":[126],"AUROC":[127,226,286],"difference":[128],"M2":[129,239,245,264],"\u2212":[130,203],"M1,":[131],"averaged":[132],"first-degree":[134],"AV":[135],"block,":[136],"right":[137],"left":[139],"bundle":[140],"branch":[141],"block":[142],"atrial":[144],"fibrillation":[145],"1":[148],"to":[149,175,210,236,281,303,310,316],"6":[150],"lost":[151,222,265,273],"(zeroed)":[152],"leads,":[153],"with":[154,189,290,324],"patient-level":[156],"paired":[157],"BCa":[158],"bootstrap":[159,191],"95%":[160,300],"confidence":[161],"interval.":[162],"Results":[163],"The":[164],"guidance":[165],"did":[166],"not":[167,337],"change":[168],"robustness:":[169],"\u0394AUROC":[170],"\u22120.0010":[171],"(95%":[172,207],"CI":[173,208,301],"\u22120.0033":[174],"+0.0006),":[176],"an":[177,312],"interval":[178,194],"entirely":[179],"within":[180],"pre-specified":[182],"\u00b10.02":[183],"margin;":[184],"result":[186],"was":[187,216,246,255],"unchanged":[188],"another":[190],"seed,":[192],"other":[193],"methods":[195],"leave-one-diagnosis-out":[197],"analyses.":[198],"Masking":[199],"improved":[200],"AUROC:":[201],"M1":[202],"M0":[204],"=":[205],"+0.0134":[206],"+0.0102":[209],"+0.0172)":[211],"when":[212,268,279],"key":[214,270],"lost,":[217],"number":[220],"tolerated":[224],"before":[225],"fell":[227],"more":[229,267],"than":[230],"0.02":[231],"rose":[232],"from":[233],"7":[234],"(M0)":[235],"(M1).":[238],"matched":[241],"non-inferior":[247],"intact":[249],"ECGs,":[250],"but":[251,327],"calibration":[253],"slope":[254],"lower":[256],"all":[258,269],"six":[259],"diagnoses":[260],"in":[261],"both":[262],"datasets.":[263],"slightly":[266],"were":[272],"together":[274],"(\u22120.0067)":[275],"gained":[277],"only":[278],"remained":[284],"(exploratory;":[285],"0.9408":[287],"vs":[288],"0.9210":[289],"11":[291],"lost).":[293],"reproduced":[295],"every":[296],"pattern":[297],"(primary":[298],"\u22120.0007,":[299],"\u22120.0011":[302],"\u22120.0003).":[304],"Conclusions":[305],"Random":[306],"suffices":[309],"make":[311],"ECG":[313],"robust":[315],"leads;":[318],"adding":[319],"guideline":[320],"aligns":[322],"criteria":[326],"no":[329],"worsens":[332],"calibration.":[333],"Guideline-aligned":[334],"should":[336],"taken":[339],"as":[340],"evidence":[341],"robustness.":[343]},"counts_by_year":[],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2026-10-20T00:00:00"}
