{"id":"https://openalex.org/W4283271862","doi":"https://doi.org/10.3390/e24060847","title":"Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study","display_name":"Using Background Knowledge from Preceding Studies for Building a Random Forest Prediction Model: A Plasmode Simulation Study","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4283271862","doi":"https://doi.org/10.3390/e24060847","pmid":"https://pubmed.ncbi.nlm.nih.gov/35741566"},"language":"en","primary_location":{"id":"doi:10.3390/e24060847","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060847","pdf_url":"https://www.mdpi.com/1099-4300/24/6/847/pdf?version=1655716423","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/24/6/847/pdf?version=1655716423","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015642516","display_name":"Lorena Hafermann","orcid":"https://orcid.org/0000-0002-2072-8539"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]},{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]},{"id":"https://openalex.org/I7877124","display_name":"Charit\u00e9 - Universit\u00e4tsmedizin Berlin","ror":"https://ror.org/001w7jn25","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I7877124"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Lorena Hafermann","raw_affiliation_strings":["Institute of Biometry and Clinical Epidemiology, Charit\u00e9\u2013Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Charit\u00e9platz 1, 10117 Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Biometry and Clinical Epidemiology, Charit\u00e9\u2013Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Charit\u00e9platz 1, 10117 Berlin, Germany","institution_ids":["https://openalex.org/I39343248","https://openalex.org/I75951250","https://openalex.org/I7877124"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009563869","display_name":"Nadja Klein","orcid":"https://orcid.org/0000-0002-5072-5347"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Nadja Klein","raw_affiliation_strings":["Chair of Statistics and Data Science, School of Business and Economics, Humboldt-Universit\u00e4t zu Berlin, Unter den Linden 6, 10099 Berlin, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5072-5347","affiliations":[{"raw_affiliation_string":"Chair of Statistics and Data Science, School of Business and Economics, Humboldt-Universit\u00e4t zu Berlin, Unter den Linden 6, 10099 Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037609806","display_name":"Geraldine Rauch","orcid":"https://orcid.org/0000-0002-2451-1660"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]},{"id":"https://openalex.org/I75951250","display_name":"Freie Universit\u00e4t Berlin","ror":"https://ror.org/046ak2485","country_code":"DE","type":"education","lineage":["https://openalex.org/I75951250"]},{"id":"https://openalex.org/I7877124","display_name":"Charit\u00e9 - Universit\u00e4tsmedizin Berlin","ror":"https://ror.org/001w7jn25","country_code":"DE","type":"healthcare","lineage":["https://openalex.org/I7877124"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Geraldine Rauch","raw_affiliation_strings":["Institute of Biometry and Clinical Epidemiology, Charit\u00e9\u2013Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Charit\u00e9platz 1, 10117 Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Biometry and Clinical Epidemiology, Charit\u00e9\u2013Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Charit\u00e9platz 1, 10117 Berlin, Germany","institution_ids":["https://openalex.org/I39343248","https://openalex.org/I75951250","https://openalex.org/I7877124"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053024693","display_name":"Michael Kammer","orcid":"https://orcid.org/0000-0003-4821-9928"},"institutions":[{"id":"https://openalex.org/I76134821","display_name":"Medical University of Vienna","ror":"https://ror.org/05n3x4p02","country_code":"AT","type":"education","lineage":["https://openalex.org/I76134821"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Michael Kammer","raw_affiliation_strings":["Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria"],"raw_orcid":"https://orcid.org/0000-0003-4821-9928","affiliations":[{"raw_affiliation_string":"Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria","institution_ids":["https://openalex.org/I76134821"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040146633","display_name":"Georg Heinze","orcid":"https://orcid.org/0000-0003-1147-8491"},"institutions":[{"id":"https://openalex.org/I76134821","display_name":"Medical University of Vienna","ror":"https://ror.org/05n3x4p02","country_code":"AT","type":"education","lineage":["https://openalex.org/I76134821"]}],"countries":["AT"],"is_corresponding":true,"raw_author_name":"Georg Heinze","raw_affiliation_strings":["Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria"],"raw_orcid":"https://orcid.org/0000-0003-1147-8491","affiliations":[{"raw_affiliation_string":"Section for Clinical Biometrics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Spitalgasse 23, 1090 Vienna, Austria","institution_ids":["https://openalex.org/I76134821"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009563869","https://openalex.org/A5040146633"],"corresponding_institution_ids":["https://openalex.org/I39343248","https://openalex.org/I76134821"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":1770,"currency":"EUR","value_usd":1908},"fwci":0.4383,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.61442139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"24","issue":"6","first_page":"847","last_page":"847"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.9976000189781189,"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":0.9976000189781189,"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/T12026","display_name":"Explainable Artificial Intelligence (XAI)","score":0.986299991607666,"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/T11918","display_name":"Forecasting Techniques and Applications","score":0.9731000065803528,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8373110294342041},{"id":"https://openalex.org/keywords/brier-score","display_name":"Brier score","score":0.8279649615287781},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.8211431503295898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6879875063896179},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6360368132591248},{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.5981625318527222},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5507602691650391},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5336160659790039},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.49894165992736816},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4576626420021057},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.45080819725990295},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.43786269426345825},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43574440479278564},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4345622956752777},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4200681746006012},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4123101532459259},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.25790780782699585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16049104928970337}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8373110294342041},{"id":"https://openalex.org/C35405484","wikidata":"https://www.wikidata.org/wiki/Q4967066","display_name":"Brier score","level":2,"score":0.8279649615287781},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.8211431503295898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6879875063896179},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6360368132591248},{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.5981625318527222},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5507602691650391},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5336160659790039},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.49894165992736816},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4576626420021057},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.45080819725990295},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.43786269426345825},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43574440479278564},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4345622956752777},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4200681746006012},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4123101532459259},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.25790780782699585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16049104928970337},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/e24060847","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060847","pdf_url":"https://www.mdpi.com/1099-4300/24/6/847/pdf?version=1655716423","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:35741566","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35741566","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:8987b6d2feb944698046a4ab0ebb8307","is_oa":true,"landing_page_url":"https://doaj.org/article/8987b6d2feb944698046a4ab0ebb8307","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 24, Iss 6, p 847 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1099-4300/24/6/847/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/e24060847","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Entropy; Volume 24; Issue 6; Pages: 847","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:9222226","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9222226","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e24060847","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e24060847","pdf_url":"https://www.mdpi.com/1099-4300/24/6/847/pdf?version=1655716423","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.6700000166893005,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G972968662","display_name":null,"funder_award_id":"I4739-B","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"}],"funders":[{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4283271862.pdf"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W1578530776","https://openalex.org/W1602160603","https://openalex.org/W1875061881","https://openalex.org/W1918662237","https://openalex.org/W1984452200","https://openalex.org/W1997963774","https://openalex.org/W2006940889","https://openalex.org/W2051177122","https://openalex.org/W2060932845","https://openalex.org/W2084341220","https://openalex.org/W2097360283","https://openalex.org/W2115709314","https://openalex.org/W2119910794","https://openalex.org/W2122825543","https://openalex.org/W2135046866","https://openalex.org/W2157395790","https://openalex.org/W2159235877","https://openalex.org/W2494169975","https://openalex.org/W2559517375","https://openalex.org/W2704876136","https://openalex.org/W2775363893","https://openalex.org/W2782176193","https://openalex.org/W2787894218","https://openalex.org/W2798958557","https://openalex.org/W2907638671","https://openalex.org/W2911964244","https://openalex.org/W2951936974","https://openalex.org/W2996480032","https://openalex.org/W3014524604","https://openalex.org/W3014535943","https://openalex.org/W3015000291","https://openalex.org/W3024192828","https://openalex.org/W3098865414","https://openalex.org/W3102027041","https://openalex.org/W3106503709","https://openalex.org/W3121452939","https://openalex.org/W3203880385","https://openalex.org/W4210798757","https://openalex.org/W4233026002","https://openalex.org/W4294541781"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4394010018","https://openalex.org/W3015383640","https://openalex.org/W4362673256","https://openalex.org/W4399653172","https://openalex.org/W2995264312"],"abstract_inverted_index":{"There":[0],"is":[1,32,70],"an":[2,202],"increasing":[3],"interest":[4],"in":[5],"machine":[6],"learning":[7],"(ML)":[8],"algorithms":[9],"for":[10,54,206],"predicting":[11],"patient":[12],"outcomes,":[13],"as":[14,109,116,201],"these":[15],"methods":[16,81,114],"are":[17],"designed":[18,33],"to":[19,34,57,72],"automatically":[20],"discover":[21],"complex":[22],"data":[23,129],"patterns.":[24],"For":[25],"example,":[26],"the":[27,92,110,151,185,194],"random":[28],"forest":[29],"(RF)":[30],"algorithm":[31],"identify":[35],"relevant":[36],"predictor":[37,145],"variables":[38],"out":[39],"of":[40,44,94,153,171,197],"a":[41,121,128,132],"large":[42],"set":[43,130],"candidates.":[45],"In":[46,87],"addition,":[47],"researchers":[48],"may":[49,82],"also":[50],"use":[51],"external":[52,85,95,160,203],"information":[53,96,204],"variable":[55,62,99],"selection":[56,63,100],"improve":[58],"model":[59,209],"interpretability":[60],"and":[61,79,142,173],"accuracy,":[64],"thereby":[65],"prediction":[66,178,208],"quality.":[67],"However,":[68,177],"it":[69],"unclear":[71],"which":[73],"extent,":[74],"if":[75],"at":[76],"all,":[77],"RF":[78,162],"ML":[80],"benefit":[83],"from":[84,97,131],"information.":[86],"this":[88],"paper,":[89],"we":[90],"examine":[91],"usefulness":[93],"prior":[98],"studies":[101,198],"that":[102,167,199],"used":[103],"traditional":[104],"statistical":[105],"modeling":[106],"approaches":[107],"such":[108,115],"Lasso,":[111],"or":[112,184],"suboptimal":[113],"univariate":[117],"selection.":[118],"We":[119,191],"conducted":[120],"plasmode":[122],"simulation":[123],"study":[124,134],"based":[125,158],"on":[126,159],"subsampling":[127],"pharmacoepidemiologic":[133],"with":[135],"nearly":[136],"200,000":[137],"individuals,":[138],"two":[139],"binary":[140],"outcomes":[141],"1152":[143],"candidate":[144,154],"(mainly":[146],"sparse":[147],"binary)":[148],"variables.":[149],"When":[150],"scope":[152],"predictors":[155],"was":[156],"reduced":[157],"knowledge":[161],"models":[163],"achieved":[164],"better":[165,169],"calibration,":[166],"is,":[168],"agreement":[170],"predictions":[172],"observed":[174],"outcome":[175],"rates.":[176],"quality":[179,196],"measured":[180],"by":[181],"cross-entropy,":[182],"AUROC":[183],"Brier":[186],"score":[187],"did":[188],"not":[189],"improve.":[190],"recommend":[192],"appraising":[193],"methodological":[195],"serve":[200],"source":[205],"future":[207],"development.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}