{"id":"https://openalex.org/W2979941711","doi":"https://doi.org/10.1109/embc.2019.8857942","title":"Application of Machine Learning to Prediction of Surgical Site Infection","display_name":"Application of Machine Learning to Prediction of Surgical Site Infection","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2979941711","doi":"https://doi.org/10.1109/embc.2019.8857942","mag":"2979941711","pmid":"https://pubmed.ncbi.nlm.nih.gov/31946345"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2019.8857942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://mediatum.ub.tum.de/node?id=1523989","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065184377","display_name":"R. Fletcher","orcid":"https://orcid.org/0000-0001-8470-8417"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard Ribon Fletcher","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075444883","display_name":"Olasubomi O. Olubeko","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Olasubomi Olubeko","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042508684","display_name":"Harsh Sonthalia","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Harsh Sonthalia","raw_affiliation_strings":["Massachusetts Institute of Technology, Cambridge, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047537947","display_name":"Fredrick Kateera","orcid":"https://orcid.org/0000-0002-6363-5180"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fredrick Kateera","raw_affiliation_strings":["Health, Kigali Rwanda"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health, Kigali Rwanda","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005191926","display_name":"Theoneste Nkurunziza","orcid":"https://orcid.org/0000-0002-5475-3396"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Theoneste Nkurunziza","raw_affiliation_strings":["Health, Kigali Rwanda"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Health, Kigali Rwanda","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009226928","display_name":"Joanna Ashby","orcid":"https://orcid.org/0000-0002-1012-0001"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joanna L. Ashby","raw_affiliation_strings":["Harvard Medical School, Boston, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040966730","display_name":"Robert Riviello","orcid":"https://orcid.org/0000-0003-3783-153X"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Riviello","raw_affiliation_strings":["Harvard Medical School, Boston, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015234622","display_name":"Bethany Hedt\u2010Gauthier","orcid":"https://orcid.org/0000-0002-9689-5413"},"institutions":[{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bethany Hedt-Gauthier","raw_affiliation_strings":["Harvard Medical School, Boston, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard Medical School, Boston, MA","institution_ids":["https://openalex.org/I136199984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9958,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.86341672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"2019","issue":null,"first_page":"2234","last_page":"2237"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11080","display_name":"Surgical site infection prevention","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11080","display_name":"Surgical site infection prevention","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12154","display_name":"Pelvic and Acetabular Injuries","score":0.9550999999046326,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11865","display_name":"Anorectal Disease Treatments and Outcomes","score":0.9433000087738037,"subfield":{"id":"https://openalex.org/subfields/2746","display_name":"Surgery"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.8467423915863037},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.708432674407959},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.6450738310813904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6041417121887207},{"id":"https://openalex.org/keywords/surgical-site-infection","display_name":"Surgical site infection","score":0.5565850734710693},{"id":"https://openalex.org/keywords/predictive-value","display_name":"Predictive value","score":0.5143010020256042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49766114354133606},{"id":"https://openalex.org/keywords/surgery","display_name":"Surgery","score":0.2700897455215454},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.2507404088973999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.23993811011314392}],"concepts":[{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.8467423915863037},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.708432674407959},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.6450738310813904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6041417121887207},{"id":"https://openalex.org/C2992582194","wikidata":"https://www.wikidata.org/wiki/Q7168672","display_name":"Surgical site infection","level":2,"score":0.5565850734710693},{"id":"https://openalex.org/C3019719930","wikidata":"https://www.wikidata.org/wiki/Q3910099","display_name":"Predictive value","level":2,"score":0.5143010020256042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49766114354133606},{"id":"https://openalex.org/C141071460","wikidata":"https://www.wikidata.org/wiki/Q40821","display_name":"Surgery","level":1,"score":0.2700897455215454},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2507404088973999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.23993811011314392}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002585","descriptor_name":"Cesarean Section","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002585","descriptor_name":"Cesarean Section","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D002585","descriptor_name":"Cesarean Section","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005544","descriptor_name":"Forecasting","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":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011247","descriptor_name":"Pregnancy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012680","descriptor_name":"Sensitivity and Specificity","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013530","descriptor_name":"Surgical Wound Infection","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013530","descriptor_name":"Surgical Wound Infection","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013530","descriptor_name":"Surgical Wound Infection","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"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":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":3,"locations":[{"id":"doi:10.1109/embc.2019.8857942","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2019.8857942","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:31946345","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31946345","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":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null},{"id":"pmh:oai:mediatum.ub.tum.de:node/1523989","is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1523989","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"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":"","raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:mediatum.ub.tum.de:node/1523989","is_oa":true,"landing_page_url":"http://mediatum.ub.tum.de/node?id=1523989","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"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":"","raw_type":"article"},"sustainable_development_goals":[{"display_name":"Good health and well-being","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1970231227","https://openalex.org/W2127592891","https://openalex.org/W2152410079","https://openalex.org/W2526066647","https://openalex.org/W2765612146","https://openalex.org/W2900490187","https://openalex.org/W6756573033"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W1531601525","https://openalex.org/W1967868727","https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W1948992892"],"abstract_inverted_index":{"Surgical":[0],"site":[1],"infections":[2],"are":[3,243],"an":[4,25,134,173,190,220],"important":[5],"health":[6],"concern,":[7],"particularly":[8],"in":[9,37,46,257],"low-resource":[10],"areas,":[11],"where":[12],"there":[13],"is":[14,51,260],"poor":[15],"access":[16],"to":[17,85],"clinical":[18,22],"facilities":[19],"or":[20],"trained":[21,96],"staff.":[23],"As":[24],"application":[26],"of":[27,43,55,163,172,252],"machine":[28,263],"learning,":[29,264],"we":[30],"present":[31],"results":[32,125],"from":[33,64,166,176,239],"a":[34,52,73,91],"study":[35,242],"conducted":[36,94],"rural":[38,258],"Rwanda":[39,259],"for":[40,111,255],"the":[41,77,112,116,120,123,129,156,161,167,170,177,180,184,216],"purpose":[42],"predicting":[44],"infection":[45,254],"Cesarean":[47],"section":[48],"wounds,":[49],"which":[50],"leading":[53],"cause":[54],"maternal":[56],"mortality.":[57],"Questionnaire":[58],"and":[59,103,115,146,169,202,213,231,246],"image":[60,117,181,214,268],"data":[61,114,182,212,269],"were":[62,83,108,126,160],"collected":[63],"572":[65,78],"mothers":[66],"approximately":[67],"10":[68],"days":[69],"after":[70],"surgery":[71],"at":[72],"district":[74],"hospital.":[75],"Of":[76],"women,":[79],"61":[80],"surgical":[81,253],"wounds":[82],"determined":[84,89],"be":[86],"infected":[87],"as":[88],"by":[90,95,128],"physical":[92],"exam":[93],"doctors.":[97],"Machine":[98],"learning":[99],"models,":[100],"logistic":[101],"regression":[102,131],"Support":[104],"Vector":[105],"Machines":[106],"(SVM),":[107],"developed":[109],"independently":[110],"questionnaire":[113,121,211],"data.":[118],"For":[119],"data,":[122,215],"best":[124],"achieved":[127,219],"Logistic":[130],"model,":[132],"with":[133,155,189],"AUC":[135,191,221],"Accuracy":[136,192,222],"=":[137,141,148,193,197,204,223,227,233],"96.50%":[138],"(93.0%-99.3%),":[139],"Sensitivity":[140,196,226],"0.71":[142],"(0.33":[143],"-":[144,151,200,207,236],"0.92),":[145],"Specificity":[147,203,232],"0.99":[149,198,205,228,234],"(0.98":[150],"1.00).":[152,208,237],"The":[153],"features":[154],"greatest":[157],"predictive":[158],"value":[159],"presence":[162,171],"malcolored":[164],"drainage":[165],"wound":[168],"odorous":[174],"discharge":[175],"wound.":[178],"Using":[179],"alone,":[183],"SVM":[185,217],"model":[186,218],"performed":[187],"best,":[188],"99.5%":[194],"(99.2%-100%),":[195],"(0.99":[199,206,229,235],"1.00),":[201],"Combining":[209],"both":[210],"99.9%":[224],"(99.7%-100%),":[225],"-1.00),":[230],"Results":[238],"this":[240],"initial":[241],"very":[244],"encouraging":[245],"demonstrate":[247],"that":[248],"good":[249],"objective":[250],"prediction":[251],"women":[256],"feasible":[261],"using":[262,267],"even":[265],"when":[266],"alone.":[270]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
