{"id":"https://openalex.org/W4320705806","doi":"https://doi.org/10.48550/arxiv.2301.06535","title":"Case-Base Neural Networks: survival analysis with time-varying, higher-order interactions","display_name":"Case-Base Neural Networks: survival analysis with time-varying, higher-order interactions","publication_year":2023,"publication_date":"2023-01-16","ids":{"openalex":"https://openalex.org/W4320705806","doi":"https://doi.org/10.48550/arxiv.2301.06535"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2301.06535","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.06535","pdf_url":"https://arxiv.org/pdf/2301.06535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2301.06535","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062742746","display_name":"Jesse Islam","orcid":"https://orcid.org/0000-0001-7500-5453"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Islam, Jesse","raw_affiliation_strings":["McGill University Department of Quantitative Life Sciences, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University Department of Quantitative Life Sciences, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076555314","display_name":"Maxime Turgeon","orcid":"https://orcid.org/0000-0003-4863-6035"},"institutions":[{"id":"https://openalex.org/I46247651","display_name":"University of Manitoba","ror":"https://ror.org/02gfys938","country_code":"CA","type":"education","lineage":["https://openalex.org/I46247651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Turgeon, Maxime","raw_affiliation_strings":["University of Manitoba Department of Statistics, 50 Sifton Rd, Winnipeg, R3T2N2, Manitoba, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Manitoba Department of Statistics, 50 Sifton Rd, Winnipeg, R3T2N2, Manitoba, Canada","institution_ids":["https://openalex.org/I46247651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005999411","display_name":"Robert Sladek","orcid":"https://orcid.org/0000-0002-2730-1204"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sladek, Robert","raw_affiliation_strings":["McGill University Department of Human Genetics, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada","McGill University Department of Quantitative Life Sciences, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University Department of Human Genetics, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada","institution_ids":["https://openalex.org/I5023651"]},{"raw_affiliation_string":"McGill University Department of Quantitative Life Sciences, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059659798","display_name":"Sahir Bhatnagar","orcid":"https://orcid.org/0000-0001-8956-2509"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bhatnagar, Sahir","raw_affiliation_strings":["McGill University Department of Biostatistics, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"McGill University Department of Biostatistics, 805 rue Sherbrooke O, Montr\u00e9al, H3A 0B9, Quebec, Canada","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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/T10136","display_name":"Statistical Methods and Inference","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.9832000136375427,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12011","display_name":"Insurance, Mortality, Demography, Risk Management","score":0.9807999730110168,"subfield":{"id":"https://openalex.org/subfields/3317","display_name":"Demography"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7542684078216553},{"id":"https://openalex.org/keywords/censoring","display_name":"Censoring (clinical trials)","score":0.7310910224914551},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6585133671760559},{"id":"https://openalex.org/keywords/covariate","display_name":"Covariate","score":0.5537652373313904},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.49286723136901855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48334547877311707},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.48126929998397827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4640103578567505},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4609532654285431},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4462950825691223},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20554107427597046},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07294577360153198}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7542684078216553},{"id":"https://openalex.org/C137668524","wikidata":"https://www.wikidata.org/wiki/Q189813","display_name":"Censoring (clinical trials)","level":2,"score":0.7310910224914551},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6585133671760559},{"id":"https://openalex.org/C119043178","wikidata":"https://www.wikidata.org/wiki/Q320723","display_name":"Covariate","level":2,"score":0.5537652373313904},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.49286723136901855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48334547877311707},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.48126929998397827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4640103578567505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4609532654285431},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4462950825691223},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20554107427597046},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07294577360153198},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2301.06535","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.06535","pdf_url":"https://arxiv.org/pdf/2301.06535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2301.06535","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2301.06535","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2301.06535","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2301.06535","pdf_url":"https://arxiv.org/pdf/2301.06535","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.699999988079071,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4320705806.pdf"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1537593861","https://openalex.org/W1570622790","https://openalex.org/W1934193819","https://openalex.org/W2052724341","https://openalex.org/W2057722879","https://openalex.org/W2080659816","https://openalex.org/W2088893370","https://openalex.org/W2095705004","https://openalex.org/W2124240218","https://openalex.org/W2125837480","https://openalex.org/W2135369095","https://openalex.org/W2146392455","https://openalex.org/W2182669574","https://openalex.org/W2253350979","https://openalex.org/W2377410957","https://openalex.org/W2582743722","https://openalex.org/W2745940724","https://openalex.org/W2753919178","https://openalex.org/W2789172526","https://openalex.org/W2797883881","https://openalex.org/W2798890825","https://openalex.org/W2805456907","https://openalex.org/W2894748956","https://openalex.org/W2943162041","https://openalex.org/W2949310256","https://openalex.org/W3010168554","https://openalex.org/W3014599079","https://openalex.org/W3028312379","https://openalex.org/W3031635948","https://openalex.org/W3036901136","https://openalex.org/W3048603078","https://openalex.org/W3083699157","https://openalex.org/W3088188126","https://openalex.org/W3119909222","https://openalex.org/W3122108726","https://openalex.org/W3137675974","https://openalex.org/W3147894994","https://openalex.org/W3169998668","https://openalex.org/W3176016422","https://openalex.org/W3194668998","https://openalex.org/W3210707002","https://openalex.org/W4205391205","https://openalex.org/W4213164367","https://openalex.org/W4214727128","https://openalex.org/W4224326349","https://openalex.org/W4239794595","https://openalex.org/W4283657134","https://openalex.org/W4285151579","https://openalex.org/W4287663858","https://openalex.org/W4287829612","https://openalex.org/W4294796663","https://openalex.org/W4315783567","https://openalex.org/W4323534069","https://openalex.org/W4386010105","https://openalex.org/W4386989161","https://openalex.org/W4388608496","https://openalex.org/W4399636375","https://openalex.org/W4399639239"],"related_works":["https://openalex.org/W2064181951","https://openalex.org/W2792777176","https://openalex.org/W2380754093","https://openalex.org/W2103018859","https://openalex.org/W4387383400","https://openalex.org/W2145919421","https://openalex.org/W1964786254","https://openalex.org/W1997403101","https://openalex.org/W1981691757","https://openalex.org/W2166421826"],"abstract_inverted_index":{"In":[0],"the":[1,54,90,102,108,166,177,182],"context":[2],"of":[3,92,110,184,201],"survival":[4,117,204],"analysis,":[5],"data-driven":[6,199],"neural":[7,60,80,115],"network-based":[8,116],"methods":[9,20,118,157],"have":[10],"been":[11],"developed":[12],"to":[13,71,100,112,145,158,191],"model":[14,32],"complex":[15,36,139,212],"covariate":[16],"effects.":[17],"While":[18],"these":[19],"may":[21],"provide":[22,192],"better":[23],"predictive":[24],"performance":[25,109,133,175],"than":[26],"regression-based":[27],"approaches,":[28],"not":[29],"all":[30,147,156],"can":[31],"time-varying":[33,143,208],"interactions":[34,144],"and":[35,68,114,122,142,172,195,210],"baseline":[37,140,213],"hazards.":[38],"To":[39],"address":[40],"this,":[41],"we":[42,76,131,154],"propose":[43],"Case-Base":[44],"Neural":[45],"Networks":[46],"(CBNNs)":[47],"as":[48,85],"a":[49,64,78,97,120,135,138,193,211],"new":[50],"approach":[51],"that":[52,82,206],"combines":[53],"case-base":[55,186],"sampling":[56,66,187],"framework":[57,197],"with":[58,149,163,188],"flexible":[59,196],"network":[61,81],"architectures.":[62],"Using":[63],"novel":[65],"scheme":[67],"data":[69,161],"augmentation":[70],"naturally":[72],"account":[73],"for":[74,198],"censoring,":[75],"construct":[77],"feed-forward":[79],"includes":[83],"time":[84],"an":[86,93],"input.":[87],"CBNNs":[88,111,164],"predict":[89],"probability":[91],"event":[94,203],"occurring":[95],"at":[96,222],"given":[98],"moment":[99],"estimate":[101],"full":[103],"hazard":[104,141,214],"function.":[105],"We":[106],"compare":[107],"regression":[113],"in":[119,169,176],"simulation":[121,136],"three":[123,159],"case":[124],"studies":[125,171],"using":[126],"two":[127,170],"time-dependent":[128],"metrics.":[129],"First,":[130],"examine":[132],"on":[134],"involving":[137],"assess":[146],"methods,":[148],"CBNN":[150],"outperforming":[151,165],"competitors.":[152],"Then,":[153],"apply":[155],"real":[160],"applications,":[162],"competing":[167],"models":[168],"showing":[173],"similar":[174],"third.":[178],"Our":[179],"results":[180],"highlight":[181],"benefit":[183],"combining":[185],"deep":[189],"learning":[190],"simple":[194],"modeling":[200],"single":[202],"outcomes":[205],"estimates":[207],"effects":[209],"by":[215],"design.":[216],"An":[217],"R":[218],"package":[219],"is":[220],"available":[221],"https://github.com/Jesse-Islam/cbnn.":[223]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}