{"id":"https://openalex.org/W4411281867","doi":"https://doi.org/10.1007/s13042-025-02666-1","title":"Causalteshap: discerning predictive from prognostic features for treatment effect analysis","display_name":"Causalteshap: discerning predictive from prognostic features for treatment effect analysis","publication_year":2025,"publication_date":"2025-06-13","ids":{"openalex":"https://openalex.org/W4411281867","doi":"https://doi.org/10.1007/s13042-025-02666-1"},"language":"en","primary_location":{"id":"doi:10.1007/s13042-025-02666-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02666-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02666-1.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02666-1.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084941141","display_name":"Jarne Verhaeghe","orcid":"https://orcid.org/0000-0002-3322-150X"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Jarne Verhaeghe","raw_affiliation_strings":["IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008111431","display_name":"Femke Ongenae","orcid":"https://orcid.org/0000-0003-2529-5477"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Femke Ongenae","raw_affiliation_strings":["IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025315149","display_name":"Sofie Van Hoecke","orcid":"https://orcid.org/0000-0002-7865-6793"},"institutions":[{"id":"https://openalex.org/I32597200","display_name":"Ghent University","ror":"https://ror.org/00cv9y106","country_code":"BE","type":"education","lineage":["https://openalex.org/I32597200"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Sofie Van Hoecke","raw_affiliation_strings":["IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium"],"affiliations":[{"raw_affiliation_string":"IDLab, Ghent University - imec, Technologiepark-Zwijnaarde, 9052, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5084941141"],"corresponding_institution_ids":["https://openalex.org/I32597200"],"apc_list":{"value":2790,"currency":"EUR","value_usd":3590},"apc_paid":{"value":2790,"currency":"EUR","value_usd":3590},"fwci":2.4915,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8850643,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"16","issue":"10","first_page":"7487","last_page":"7507"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9991999864578247,"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9991999864578247,"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/T10804","display_name":"Health Systems, Economic Evaluations, Quality of Life","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11235","display_name":"Statistical Methods in Clinical Trials","score":0.9961000084877014,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.6701362133026123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4676002860069275},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43352657556533813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3362852931022644}],"concepts":[{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.6701362133026123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4676002860069275},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43352657556533813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3362852931022644}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s13042-025-02666-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02666-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02666-1.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},{"id":"pmh:oai:archive.ugent.be:01JXW61MNTF5HGF52PK4Q1A1EN","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-01JXW61MNTF5HGF52PK4Q1A1EN","pdf_url":"https://biblio.ugent.be/publication/01JXW61MNTF5HGF52PK4Q1A1EN/file/01K9ET8D2NY17CBQSHARG65WHP.pdf","source":{"id":"https://openalex.org/S4306400478","display_name":"Ghent University Academic Bibliography (Ghent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I32597200","host_organization_name":"Ghent University","host_organization_lineage":["https://openalex.org/I32597200"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISSN: 1868-808X","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1007/s13042-025-02666-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s13042-025-02666-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s13042-025-02666-1.pdf","source":{"id":"https://openalex.org/S2764999920","display_name":"International Journal of Machine Learning and Cybernetics","issn_l":"1868-8071","issn":["1868-8071","1868-808X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Machine Learning and Cybernetics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G173144583","display_name":null,"funder_award_id":"G085920N)","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G2015697915","display_name":null,"funder_award_id":"1S59522N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G7392831411","display_name":null,"funder_award_id":"G085920N","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"},{"id":"https://openalex.org/G8936651487","display_name":null,"funder_award_id":"1S59522N).","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320327336","display_name":"Vlaamse regering","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4411281867.pdf","grobid_xml":"https://content.openalex.org/works/W4411281867.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1516659296","https://openalex.org/W2003336670","https://openalex.org/W2011087402","https://openalex.org/W2056526977","https://openalex.org/W2062989416","https://openalex.org/W2103683880","https://openalex.org/W2130939988","https://openalex.org/W2140435154","https://openalex.org/W2153646525","https://openalex.org/W2158485828","https://openalex.org/W2168991419","https://openalex.org/W2265453572","https://openalex.org/W2624816748","https://openalex.org/W2713480577","https://openalex.org/W2797921591","https://openalex.org/W2921398811","https://openalex.org/W2964261049","https://openalex.org/W3071516413","https://openalex.org/W3116286104","https://openalex.org/W3124999902","https://openalex.org/W3131505924","https://openalex.org/W3186962463","https://openalex.org/W3201378459","https://openalex.org/W4229626909","https://openalex.org/W4233948102","https://openalex.org/W4310170174","https://openalex.org/W4311757692","https://openalex.org/W4312791840","https://openalex.org/W4327656748","https://openalex.org/W4367057227","https://openalex.org/W4394964969"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Abstract":[0],"Treatment":[1],"effect":[2,6,19,49,121,173,193,206,227],"analysis":[3,228],"investigates":[4],"the":[5,17,28,47,61,85,167,172,180,184,201],"of":[7,31,41,64,88,93,144,174,186,203],"a":[8,65,89,111,161,189,216],"treatment":[9,18,48,66,120,192,205,226,232],"or":[10,67],"intervention.":[11],"The":[12,39,129],"variables":[13,26,104],"that":[14,114,198],"will":[15],"determine":[16,27],"are":[20,69,78],"called,":[21],"predictive":[22,43,62,76,86,95,103,127,221],"variables,":[23],"while":[24],"prognostic":[25,97,125,223],"outcome":[29],"regardless":[30],"treatment,":[32],"based":[33],"on":[34,37,83,133,176],"existing":[35],"conditions":[36],"characteristics.":[38],"identification":[40],"these":[42,75,102,145],"factors":[44,63,77],"facilitates":[45],"understanding":[46,231],"and":[50,80,119,138,151,211,229],"even":[51],"allows":[52],"for":[53,191,219],"improving":[54],"its":[55],"success.":[56],"However,":[57],"in":[58,179,225],"many":[59],"cases,":[60],"intervention":[68],"unknown.":[70],"Furthermore,":[71],"methods":[72],"to":[73,100,123,160,182,214],"find":[74,101],"limited":[79],"only":[81],"focus":[82],"quantifying":[84],"performance":[87],"CATE":[90],"estimator":[91],"instead":[92],"discerning":[94,220],"from":[96,126,222],"variables.":[98],"Therefore,":[99],"we":[105],"present":[106],"Causalteshap":[107,109,147,157,187,199],".":[108],"is":[110,131,158],"Shapley-based":[112],"method":[113,130,218],"leverages":[115],"multiple":[116,134],"statistical":[117,212],"tests":[118,213],"estimators":[122,207],"discern":[124],"features.":[128],"benchmarked":[132],"fully":[135],"synthetic":[136],"datasets":[137],"four":[139],"semi-synthetic":[140],"datasets.":[141],"In":[142],"most":[143],"benchmarks,":[146],"demonstrates":[148],"high":[149],"precision":[150],"recall":[152],"performances":[153],"above":[154],"0.9.":[155],"Subsequently,":[156],"applied":[159],"real-world":[162],"ICU":[163,181],"use":[164],"case":[165],"using":[166],"AmsterdamUMCdb":[168],"dataset.":[169],"We":[170],"analyzed":[171],"Noradrenaline":[175],"Atrial":[177],"Fibrillation":[178],"display":[183],"potential":[185,202],"as":[188],"tool":[190],"analysis.":[194],"Our":[195],"results":[196],"demonstrate":[197],"has":[200],"combining":[204],"with":[208],"Shapley":[209],"values":[210],"provide":[215],"novel":[217],"features":[224],"making":[230],"effects":[233],"more":[234],"accessible.":[235]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}