{"id":"https://openalex.org/W4319453332","doi":"https://doi.org/10.48550/arxiv.2302.02560","title":"Causal Estimation of Exposure Shifts with Neural Networks: Evaluating the Health Benefits of Stricter Air Quality Standards in the US","display_name":"Causal Estimation of Exposure Shifts with Neural Networks: Evaluating the Health Benefits of Stricter Air Quality Standards in the US","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4319453332","doi":"https://doi.org/10.48550/arxiv.2302.02560"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.02560","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2302.02560","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5081042936","display_name":"Mauricio Tec","orcid":"https://orcid.org/0000-0002-1853-5842"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tec, Mauricio","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078659514","display_name":"Oladimeji Mudele","orcid":"https://orcid.org/0000-0001-7131-6334"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mudele, Oladimeji","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051444314","display_name":"Kevin Josey","orcid":"https://orcid.org/0000-0003-2490-6272"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Josey, Kevin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5007008626","display_name":"Francesca Dominici","orcid":"https://orcid.org/0000-0002-9382-0141"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dominici, Francesca","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":67},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.9659,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10190","display_name":"Air Quality and Health Impacts","score":0.9659,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness","score":0.5831978}],"concepts":[{"id":"https://openalex.org/C158600405","wikidata":"https://www.wikidata.org/wiki/Q5054566","display_name":"Causal inference","level":2,"score":0.65091723},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.58703315},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5831978},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.58184123},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4876403},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47769836},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.30599985},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25697818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2518658},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.02560","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.02560","pdf_url":"http://arxiv.org/pdf/2302.02560","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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2302.02560","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2302.02560","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":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4385769873","https://openalex.org/W4366700029","https://openalex.org/W4319161863","https://openalex.org/W4311888330","https://openalex.org/W4307819175","https://openalex.org/W4287880334","https://openalex.org/W4285230481","https://openalex.org/W4281634296","https://openalex.org/W2371687270","https://openalex.org/W2015759683"],"abstract_inverted_index":{"In":[0],"policy":[1],"research,":[2],"one":[3],"of":[4,16,23,30,92,223],"the":[5,13,21,101,105,110,136,148,151,182,220],"most":[6],"critical":[7],"analytic":[8],"tasks":[9],"is":[10,144],"to":[11,20,76,89,103,125,145,181,225],"estimate":[12,77,104],"causal":[14,106,163,187],"effect":[15,107],"a":[17,24,59,68,195],"policy-relevant":[18,61],"shift":[19],"distribution":[22],"continuous":[25],"exposure/treatment":[26],"on":[27],"an":[28],"outcome":[29,228],"interest.":[31],"We":[32,84,236],"call":[33],"this":[34,159],"problem":[35],"shift-response":[36],"function":[37],"(SRF)":[38],"estimation.":[39,56],"Existing":[40],"neural":[41,69,183],"network":[42,70,184],"methods":[43,164],"involving":[44],"robust":[45],"causal-effect":[46],"estimators":[47],"lack":[48],"theoretical":[49,74,200],"guarantees":[50],"and":[51,72,81,96,206,248],"practical":[52],"implementations":[53],"for":[54,118,147,165,173,186,211],"SRF":[55,212],"Motivated":[57],"by":[58,135],"key":[60],"question":[62],"in":[63,153,189],"public":[64],"health,":[65],"we":[66],"develop":[67],"method":[71,88],"its":[73],"underpinnings":[75],"SRFs":[78],"with":[79,176,199,240],"robustness":[80,205],"efficiency":[82,209],"guarantees.":[83],"then":[85],"apply":[86],"our":[87,238],"data":[90],"consisting":[91],"68":[93],"million":[94,98],"individuals":[95],"27":[97],"deaths":[99,154],"across":[100],"U.S.":[102],"from":[108,121,158,219],"revising":[109],"US":[111,137],"National":[112],"Ambient":[113],"Air":[114],"Quality":[115],"Standards":[116],"(NAAQS)":[117],"PM":[119],"2.5":[120],"12":[122],"$\\mu":[123,127],"g/m^3$":[124],"9":[126],"g/m^3$.":[128],"This":[129],"change":[130],"has":[131],"been":[132],"recently":[133],"proposed":[134,168],"Environmental":[138],"Protection":[139],"Agency":[140],"(EPA).":[141],"Our":[142,167],"goal":[143],"estimate,":[146],"first":[149],"time,":[150],"reduction":[152],"that":[155,202,243],"would":[156],"result":[157],"anticipated":[160],"revision":[161],"using":[162],"SRFs.":[166],"method,":[169],"called":[170],"{T}argeted":[171],"{R}egularization":[172],"{E}xposure":[174],"{S}hifts":[175],"Neural":[177],"{Net}works":[178],"(TRESNET),":[179],"contributes":[180],"literature":[185],"inference":[188],"two":[190],"ways:":[191],"first,":[192],"it":[193,215],"proposes":[194],"targeted":[196],"regularization":[197],"loss":[198,217],"properties":[201],"ensure":[203],"double":[204],"achieves":[207],"asymptotic":[208],"specific":[210],"estimation;":[213],"second,":[214],"enables":[216],"functions":[218],"exponential":[221],"family":[222],"distributions":[224,229],"accommodate":[226],"non-continuous":[227],"(such":[230],"as":[231],"hospitalization":[232],"or":[233],"mortality":[234],"counts).":[235],"complement":[237],"application":[239],"benchmark":[241],"experiments":[242],"demonstrate":[244],"TRESNET's":[245],"broad":[246],"applicability":[247],"competitiveness.":[249]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4319453332","counts_by_year":[],"updated_date":"2025-01-05T00:17:51.523119","created_date":"2023-02-09"}