{"id":"https://openalex.org/W2913035889","doi":"https://doi.org/10.1109/bigdata.2018.8622627","title":"Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare","display_name":"Privacy-Preserving Scoring of Tree Ensembles: A Novel Framework for AI in Healthcare","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2913035889","doi":"https://doi.org/10.1109/bigdata.2018.8622627","mag":"2913035889"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622627","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://biblio.ugent.be/publication/8629565/file/8629566.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5091394688","display_name":"Kyle Fritchman","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150356","display_name":"University of Washington Tacoma","ror":"https://ror.org/05n8t2628","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701","https://openalex.org/I4210150356"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Fritchman","raw_affiliation_strings":["Institute of Technology, University of Washington, Tacoma, Washington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Technology, University of Washington, Tacoma, Washington, USA","institution_ids":["https://openalex.org/I4210150356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018313322","display_name":"Keerthanaa Saminathan","orcid":null},"institutions":[{"id":"https://openalex.org/I4210150356","display_name":"University of Washington Tacoma","ror":"https://ror.org/05n8t2628","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701","https://openalex.org/I4210150356"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keerthanaa Saminathan","raw_affiliation_strings":["Institute of Technology, University of Washington, Tacoma, Washington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Technology, University of Washington, Tacoma, Washington, USA","institution_ids":["https://openalex.org/I4210150356"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014034048","display_name":"Rafael Dowsley","orcid":"https://orcid.org/0000-0002-7588-2410"},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Rafael Dowsley","raw_affiliation_strings":["Dept. of Computer Science, Aarhus University, Aarhus, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science, Aarhus University, Aarhus, Denmark","institution_ids":["https://openalex.org/I204337017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020714759","display_name":"Tyler W. Hughes","orcid":"https://orcid.org/0000-0001-7989-0891"},"institutions":[{"id":"https://openalex.org/I4210115859","display_name":"Behavioral Tech Research, Inc.","ror":"https://ror.org/02843s885","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210115859"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tyler Hughes","raw_affiliation_strings":["KenSci, Seattle, Washington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KenSci, Seattle, Washington, USA","institution_ids":["https://openalex.org/I4210115859"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056749857","display_name":"Martine De Cock","orcid":"https://orcid.org/0000-0001-7917-0771"},"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":"Martine De Cock","raw_affiliation_strings":["Dept. of Applied Math., Comp. Science and Statistics, Ghent University, Ghent, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Applied Math., Comp. Science and Statistics, Ghent University, Ghent, Belgium","institution_ids":["https://openalex.org/I32597200"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070505291","display_name":"Anderson C. A. Nascimento","orcid":"https://orcid.org/0000-0002-8298-6250"},"institutions":[{"id":"https://openalex.org/I4210150356","display_name":"University of Washington Tacoma","ror":"https://ror.org/05n8t2628","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701","https://openalex.org/I4210150356"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Anderson Nascimento","raw_affiliation_strings":["Institute of Technology, University of Washington, Tacoma, Washington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Technology, University of Washington, Tacoma, Washington, USA","institution_ids":["https://openalex.org/I4210150356"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061359226","display_name":"Ankur Teredesai","orcid":"https://orcid.org/0000-0002-2112-5895"},"institutions":[{"id":"https://openalex.org/I4210115859","display_name":"Behavioral Tech Research, Inc.","ror":"https://ror.org/02843s885","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210115859"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankur Teredesai","raw_affiliation_strings":["KenSci, Seattle, Washington, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"KenSci, Seattle, Washington, USA","institution_ids":["https://openalex.org/I4210115859"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.8722,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.92932066,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2413","last_page":"2422"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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/T10237","display_name":"Cryptography and Data Security","score":0.9995999932289124,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9681000113487244,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/computer-science","display_name":"Computer science","score":0.8163427710533142},{"id":"https://openalex.org/keywords/encryption","display_name":"Encryption","score":0.6639368534088135},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6587145328521729},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5718527436256409},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.525833010673523},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5199781060218811},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5022745132446289},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.5005404949188232},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4720913767814636},{"id":"https://openalex.org/keywords/cryptography","display_name":"Cryptography","score":0.43724146485328674},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4330381155014038},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4314382076263428},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.40264761447906494},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.1867753267288208},{"id":"https://openalex.org/keywords/software-engineering","display_name":"Software engineering","score":0.12418842315673828}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8163427710533142},{"id":"https://openalex.org/C148730421","wikidata":"https://www.wikidata.org/wiki/Q141090","display_name":"Encryption","level":2,"score":0.6639368534088135},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6587145328521729},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5718527436256409},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.525833010673523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5199781060218811},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5022745132446289},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.5005404949188232},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4720913767814636},{"id":"https://openalex.org/C178489894","wikidata":"https://www.wikidata.org/wiki/Q8789","display_name":"Cryptography","level":2,"score":0.43724146485328674},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4330381155014038},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4314382076263428},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.40264761447906494},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.1867753267288208},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.12418842315673828},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/bigdata.2018.8622627","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622627","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"},{"id":"pmh:oai:archive.ugent.be:8629565","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-8629565","pdf_url":"https://biblio.ugent.be/publication/8629565/file/8629566.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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9781538650356","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:digitalcommons.tacoma.uw.edu:tech_pub-1344","is_oa":false,"landing_page_url":"https://digitalcommons.tacoma.uw.edu/tech_pub/345","pdf_url":null,"source":{"id":"https://openalex.org/S4306400628","display_name":"University of Washington Tacoma Digital Commons (University of Washington Tacoma)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210150356","host_organization_name":"University of Washington Tacoma","host_organization_lineage":["https://openalex.org/I4210150356"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"School of Engineering and Technology Publications","raw_type":"text"},{"id":"pmh:oai:pure.atira.dk:publications/f3a7a98a-b791-4857-bded-514ae90b4ddf","is_oa":false,"landing_page_url":"https://pure.au.dk/portal/en/publications/f3a7a98a-b791-4857-bded-514ae90b4ddf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fritchman, K, Saminathan, K, Dowsley, R, Hughes, T, De Cock, M, Nascimento, A & Teredesai, A 2019, Privacy-Preserving Scoring of Tree Ensembles : A Novel Framework for AI in Healthcare. in Y Song, B Liu, K Lee, N Abe, C Pu, M Qiao, N Ahmed, D Kossmann, J Saltz, J Tang, J He, H Liu & X Hu (eds), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018., 8622627, IEEE, pp. 2413-2422, 2018 IEEE International Conference on Big Data, Big Data 2018, Seattle, United States, 10/12/2018. https://doi.org/10.1109/BigData.2018.8622627","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:archive.ugent.be:8629565","is_oa":true,"landing_page_url":"http://hdl.handle.net/1854/LU-8629565","pdf_url":"https://biblio.ugent.be/publication/8629565/file/8629566.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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9781538650356","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2554276906","display_name":"Scalable Oblivious Data Analytics","funder_award_id":"731583","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"},{"id":"https://openalex.org/G5530824169","display_name":"Better MPC Protocols in Theory and in Practice","funder_award_id":"669255","funder_id":"https://openalex.org/F4320320300","funder_display_name":"European Commission"}],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2913035889.pdf","grobid_xml":"https://content.openalex.org/works/W2913035889.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W20180677","https://openalex.org/W102674675","https://openalex.org/W184146824","https://openalex.org/W1499934958","https://openalex.org/W1508764330","https://openalex.org/W1524288918","https://openalex.org/W1534477342","https://openalex.org/W1595357546","https://openalex.org/W1605455630","https://openalex.org/W1935182841","https://openalex.org/W1971991172","https://openalex.org/W1973137277","https://openalex.org/W1996796871","https://openalex.org/W2002352982","https://openalex.org/W2010317729","https://openalex.org/W2010989618","https://openalex.org/W2016519398","https://openalex.org/W2031738616","https://openalex.org/W2045597647","https://openalex.org/W2051267297","https://openalex.org/W2109426455","https://openalex.org/W2117333593","https://openalex.org/W2156800337","https://openalex.org/W2296500841","https://openalex.org/W2296539003","https://openalex.org/W2346967072","https://openalex.org/W2397857137","https://openalex.org/W2398935881","https://openalex.org/W2461943168","https://openalex.org/W2573908344","https://openalex.org/W2610250845","https://openalex.org/W2624056253","https://openalex.org/W2962835266","https://openalex.org/W2964318098","https://openalex.org/W6600841100","https://openalex.org/W6630470381","https://openalex.org/W6631325483","https://openalex.org/W6677213213","https://openalex.org/W6697105876","https://openalex.org/W6737230392","https://openalex.org/W6739604033"],"related_works":["https://openalex.org/W2770234245","https://openalex.org/W96612179","https://openalex.org/W4229499248","https://openalex.org/W2566006169","https://openalex.org/W1567818861","https://openalex.org/W2987774938","https://openalex.org/W4256492088","https://openalex.org/W632915154","https://openalex.org/W2055733372","https://openalex.org/W3022067003"],"abstract_inverted_index":{"Machine":[0],"Learning":[1],"(ML)":[2],"techniques":[3],"now":[4],"impact":[5],"a":[6,99,108,141],"wide":[7],"variety":[8],"of":[9,61,83,160,182],"domains.":[10],"Highly":[11],"regulated":[12,44],"industries":[13,45],"such":[14,189],"as":[15],"healthcare":[16,100,152],"and":[17,22,112,158,175],"finance":[18],"have":[19],"stringent":[20],"compliance":[21],"data":[23,27,52,105],"governance":[24],"policies":[25],"around":[26],"sharing.":[28],"Advances":[29],"in":[30,88,125,140,171],"secure":[31,177],"multiparty":[32],"computation":[33],"(SMC)":[34],"for":[35,80,151,163,197],"privacy-preserving":[36,81,194],"machine":[37,195],"learning":[38,196],"(PPML)":[39],"can":[40],"help":[41],"transform":[42],"these":[43,138],"by":[46],"allowing":[47],"ML":[48,109,149],"computations":[49],"over":[50],"encrypted":[51,104,114],"with":[53,86,147,192],"personally":[54],"identifiable":[55],"information":[56],"(PII).":[57],"Yet":[58],"very":[59,77],"little":[60],"SMC-based":[62,193],"PPML":[63],"has":[64],"been":[65],"put":[66],"into":[67],"practice":[68],"so":[69],"far.":[70],"In":[71],"this":[72,185],"paper":[73],"we":[74,134],"present":[75],"the":[76,93,118,126,131,180,187],"first":[78,91,188],"framework":[79,191],"classification":[82],"tree":[84],"ensembles":[85],"application":[87],"healthcare.":[89,198],"We":[90,128],"describe":[92,130],"underlying":[94],"cryptographic":[95],"protocols":[96,139],"that":[97,123],"enable":[98],"organization":[101],"to":[102,107,136,166],"send":[103],"securely":[106],"scoring":[110,119],"service":[111,120],"obtain":[113],"class":[115],"labels":[116],"without":[117],"actually":[121],"seeing":[122],"input":[124],"clear.":[127],"then":[129],"deployment":[132,162],"challenges":[133],"solved":[135],"integrate":[137],"cloud":[142],"based":[143],"scalable":[144],"risk-prediction":[145],"platform":[146],"multiple":[148],"models":[150],"AI.":[153],"Included":[154],"are":[155],"system":[156],"internals,":[157],"evaluations":[159],"our":[161,183],"supporting":[164],"physicians":[165],"drive":[167],"better":[168],"clinical":[169],"outcomes":[170],"an":[172],"accurate,":[173],"scalable,":[174],"provably":[176],"manner.":[178],"To":[179],"best":[181],"knowledge,":[184],"is":[186],"applied":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-19T17:40:00.097472","created_date":"2025-10-10T00:00:00"}