{"id":"https://openalex.org/W3129758832","doi":"https://doi.org/10.1093/jamia/ocaa346","title":"Deep propensity network using a sparse autoencoder for estimation of treatment effects","display_name":"Deep propensity network using a sparse autoencoder for estimation of treatment effects","publication_year":2020,"publication_date":"2020-12-29","ids":{"openalex":"https://openalex.org/W3129758832","doi":"https://doi.org/10.1093/jamia/ocaa346","mag":"3129758832","pmid":"https://pubmed.ncbi.nlm.nih.gov/33594415"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocaa346","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocaa346","pdf_url":"https://academic.oup.com/jamia/article-pdf/28/6/1197/38615544/ocaa346.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://academic.oup.com/jamia/article-pdf/28/6/1197/38615544/ocaa346.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021264901","display_name":"Shantanu Ghosh","orcid":"https://orcid.org/0000-0003-4085-541X"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shantanu Ghosh","raw_affiliation_strings":["Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science and Engineering, University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030951014","display_name":"Jiang Bian","orcid":"https://orcid.org/0000-0002-2238-5429"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiang Bian","raw_affiliation_strings":["Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA"],"raw_orcid":"https://orcid.org/0000-0002-2238-5429","affiliations":[{"raw_affiliation_string":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052505769","display_name":"Yi Guo","orcid":"https://orcid.org/0000-0003-0587-4105"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Guo","raw_affiliation_strings":["Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039419132","display_name":"Mattia Prosperi","orcid":"https://orcid.org/0000-0002-9021-5595"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]},{"id":"https://openalex.org/I94062374","display_name":"Florida College","ror":"https://ror.org/010bgev76","country_code":"US","type":"education","lineage":["https://openalex.org/I94062374"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mattia Prosperi","raw_affiliation_strings":["Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA"],"raw_orcid":"https://orcid.org/0000-0002-9021-5595","affiliations":[{"raw_affiliation_string":"Department of Epidemiology, College of Public Health and Health Professions & College of Medicine, University of Florida, Gainesville, Florida, USA","institution_ids":["https://openalex.org/I33213144","https://openalex.org/I94062374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039419132"],"corresponding_institution_ids":["https://openalex.org/I33213144","https://openalex.org/I94062374"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":null,"fwci":1.3989,"has_fulltext":true,"cited_by_count":15,"citation_normalized_percentile":{"value":0.83934739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":"6","first_page":"1197","last_page":"1206"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9957000017166138,"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":0.9957000017166138,"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":0.0005000000237487257,"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/T11303","display_name":"Bayesian Modeling and Causal Inference","score":0.0003000000142492354,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.8266456127166748},{"id":"https://openalex.org/keywords/propensity-score-matching","display_name":"Propensity score matching","score":0.7923406362533569},{"id":"https://openalex.org/keywords/causal-inference","display_name":"Causal inference","score":0.6615390181541443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6470576524734497},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6202072501182556},{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.6178259253501892},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.573997437953949},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.5088432431221008},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4848521947860718},{"id":"https://openalex.org/keywords/observational-study","display_name":"Observational study","score":0.47342661023139954},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4721015989780426},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4463540315628052},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.44375061988830566},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4109441936016083},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24641874432563782},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11486560106277466}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8266456127166748},{"id":"https://openalex.org/C17923572","wikidata":"https://www.wikidata.org/wiki/Q7250160","display_name":"Propensity score matching","level":2,"score":0.7923406362533569},{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.6615390181541443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6470576524734497},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6202072501182556},{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.6178259253501892},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.573997437953949},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.5088432431221008},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4848521947860718},{"id":"https://openalex.org/C23131810","wikidata":"https://www.wikidata.org/wiki/Q818574","display_name":"Observational study","level":2,"score":0.47342661023139954},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4721015989780426},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4463540315628052},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.44375061988830566},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4109441936016083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24641874432563782},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11486560106277466},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003198","descriptor_name":"Computer Simulation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011446","descriptor_name":"Prospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011446","descriptor_name":"Prospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D011446","descriptor_name":"Prospective Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D015982","descriptor_name":"Bias","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015982","descriptor_name":"Bias","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015982","descriptor_name":"Bias","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015984","descriptor_name":"Causality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015984","descriptor_name":"Causality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015984","descriptor_name":"Causality","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016015","descriptor_name":"Logistic Models","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057216","descriptor_name":"Propensity Score","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057216","descriptor_name":"Propensity Score","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D057216","descriptor_name":"Propensity Score","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocaa346","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocaa346","pdf_url":"https://academic.oup.com/jamia/article-pdf/28/6/1197/38615544/ocaa346.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:33594415","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33594415","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":"Journal of the American Medical Informatics Association : JAMIA","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8661404","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8661404","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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1093/jamia/ocaa346","is_oa":true,"landing_page_url":"https://doi.org/10.1093/jamia/ocaa346","pdf_url":"https://academic.oup.com/jamia/article-pdf/28/6/1197/38615544/ocaa346.pdf","source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.41999998688697815,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"},{"score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1087744453","display_name":null,"funder_award_id":"U18DP006512","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G1661017505","display_name":null,"funder_award_id":"R21 AG068717","funder_id":"https://openalex.org/F4320337337","funder_display_name":"National Institute on Aging"},{"id":"https://openalex.org/G3535441628","display_name":null,"funder_award_id":"R01 CA246418","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"},{"id":"https://openalex.org/G3752933254","display_name":null,"funder_award_id":"R21AG068717","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G4298683003","display_name":null,"funder_award_id":"U18 DP006512","funder_id":"https://openalex.org/F4320337383","funder_display_name":"National Center for Chronic Disease Prevention and Health Promotion"},{"id":"https://openalex.org/G4712549489","display_name":null,"funder_award_id":"R21CA245858","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G7216562522","display_name":null,"funder_award_id":"R01AI145552","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8509218437","display_name":null,"funder_award_id":"R01CA246418","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G8910645728","display_name":null,"funder_award_id":"R01 AI145552","funder_id":"https://openalex.org/F4320337355","funder_display_name":"National Institute of Allergy and Infectious Diseases"},{"id":"https://openalex.org/G915122787","display_name":null,"funder_award_id":"R21 CA245858","funder_id":"https://openalex.org/F4320337351","funder_display_name":"National Cancer Institute"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"},{"id":"https://openalex.org/F4320337337","display_name":"National Institute on Aging","ror":"https://ror.org/049v75w11"},{"id":"https://openalex.org/F4320337351","display_name":"National Cancer Institute","ror":"https://ror.org/040gcmg81"},{"id":"https://openalex.org/F4320337355","display_name":"National Institute of Allergy and Infectious Diseases","ror":"https://ror.org/043z4tv69"},{"id":"https://openalex.org/F4320337383","display_name":"National Center for Chronic Disease Prevention and Health Promotion","ror":"https://ror.org/021rths28"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3129758832.pdf","grobid_xml":"https://content.openalex.org/works/W3129758832.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1515828664","https://openalex.org/W1516659296","https://openalex.org/W1580457945","https://openalex.org/W1967862917","https://openalex.org/W1973631422","https://openalex.org/W1989377468","https://openalex.org/W2000991311","https://openalex.org/W2028426093","https://openalex.org/W2064903582","https://openalex.org/W2079224763","https://openalex.org/W2095705004","https://openalex.org/W2100495367","https://openalex.org/W2102409316","https://openalex.org/W2109247912","https://openalex.org/W2120199131","https://openalex.org/W2122532950","https://openalex.org/W2130938947","https://openalex.org/W2132917208","https://openalex.org/W2150291618","https://openalex.org/W2151688269","https://openalex.org/W2319983832","https://openalex.org/W2750575765","https://openalex.org/W2800369883","https://openalex.org/W2807044098","https://openalex.org/W2808880546","https://openalex.org/W2810580937","https://openalex.org/W2906694199","https://openalex.org/W2940818567","https://openalex.org/W2971690404","https://openalex.org/W2995109209","https://openalex.org/W3017019970","https://openalex.org/W3024173558","https://openalex.org/W3027247167","https://openalex.org/W3041564249","https://openalex.org/W3123582712","https://openalex.org/W3125108970","https://openalex.org/W4236966694","https://openalex.org/W4239728164","https://openalex.org/W6674330103","https://openalex.org/W6675401909","https://openalex.org/W6743499796","https://openalex.org/W6761626574","https://openalex.org/W6765434343"],"related_works":["https://openalex.org/W4385077270","https://openalex.org/W2889343356","https://openalex.org/W4313901042","https://openalex.org/W4214907927","https://openalex.org/W3134479707","https://openalex.org/W4287905842","https://openalex.org/W174071147","https://openalex.org/W3212910376","https://openalex.org/W2920490282","https://openalex.org/W3129758832"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Drawing":[1],"causal":[2,22],"estimates":[3],"from":[4,92,103],"observational":[5],"data":[6],"is":[7,25,205],"problematic,":[8],"because":[9,228],"datasets":[10],"often":[11],"contain":[12],"underlying":[13],"bias":[14,87],"(eg,":[15],"discrimination":[16],"in":[17,135,144,241],"treatment":[18,62,69,85,139,151,183,220,242],"assignment).":[19],"To":[20],"examine":[21],"effects,":[23,140],"it":[24],"important":[26],"to":[27,186,197],"evaluate":[28],"what-if":[29],"scenarios-the":[30],"so-called":[31],"\"counterfactuals.\"":[32],"We":[33,74,109],"propose":[34],"a":[35,51,80,100],"novel":[36],"deep":[37,47,124,178],"learning":[38,179],"architecture":[39],"for":[40,219],"propensity":[41,48,128],"score":[42],"matching":[43],"and":[44,64,88,96,99,119,149,166,170,199,238],"counterfactual":[45,90,125],"prediction-the":[46],"network":[49],"using":[50,224],"sparse":[52,214],"autoencoder":[53],"(DPN-SA)-to":[54],"tackle":[55],"the":[56,93,104,114,154,187],"problems":[57],"of":[58,113,137,201],"high":[59],"dimensionality,":[60],"nonlinear/nonparallel":[61,84],"assignment,":[63],"residual":[65],"confounding":[66],"when":[67],"estimating":[68],"effects.":[70],"MATERIALS":[71],"AND":[72,211],"METHODS:":[73],"used":[75],"2":[76],"randomized":[77],"prospective":[78],"datasets,":[79],"semisynthetic":[81],"one":[82],"with":[83,127,190],"selection":[86],"simulated":[89],"outcomes":[91],"Infant":[94],"Health":[95],"Development":[97],"Program":[98],"real-world":[101],"dataset":[102],"LaLonde's":[105],"employment":[106],"training":[107],"program.":[108],"compared":[110],"different":[111],"configurations":[112],"DPN-SA":[115,162],"against":[116],"logistic":[117,164],"regression":[118,165],"LASSO":[120,167],"as":[121,123],"well":[122],"networks":[126],"dropout":[129],"(DCN-PD).":[130],"Models'":[131],"performances":[132],"were":[133,194],"assessed":[134],"terms":[136],"average":[138,150,182],"mean":[141],"squared":[142],"error":[143],"precision":[145],"on":[146,153],"effect's":[147],"heterogeneity,":[148],"effect":[152,221],"treated,":[155],"over":[156],"multiple":[157],"training/test":[158],"runs.":[159],"RESULTS:":[160],"The":[161],"outperformed":[163],"by":[168,172],"36%-63%,":[169],"DCN-PD":[171],"6%-10%":[173],"across":[174],"all":[175],"datasets.":[176],"All":[177],"architectures":[180],"yielded":[181],"effects":[184],"close":[185],"true":[188],"ones":[189],"low":[191],"variance.":[192],"Results":[193],"also":[195],"robust":[196],"noise-injection":[198],"addition":[200],"correlated":[202],"variables.":[203],"Code":[204],"publicly":[206],"available":[207],"at":[208],"https://github.com/Shantanu48114860/DPN-SAz.":[209],"DISCUSSION":[210],"CONCLUSION:":[212],"Deep":[213],"autoencoders":[215],"are":[216],"particularly":[217],"suited":[218],"estimation":[222],"studies":[223],"electronic":[225],"health":[226],"records":[227],"they":[229],"can":[230],"handle":[231],"high-dimensional":[232],"covariate":[233],"sets,":[234],"large":[235],"sample":[236],"sizes,":[237],"complex":[239],"heterogeneity":[240],"assignments.":[243]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}