{"id":"https://openalex.org/W4407839726","doi":"https://doi.org/10.3233/978-1-60750-928-8-493","title":"Automatic Identification of Patients Eligible for a Pneumonia Guideline: Comparing the Diagnostic Accuracy of Two Decision Support Models","display_name":"Automatic Identification of Patients Eligible for a Pneumonia Guideline: Comparing the Diagnostic Accuracy of Two Decision Support Models","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W4407839726","doi":"https://doi.org/10.3233/978-1-60750-928-8-493"},"language":"en","primary_location":{"id":"doi:10.3233/978-1-60750-928-8-493","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-60750-928-8-493","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Lagor Charles","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lagor Charles","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116378948","display_name":"Aronsky Dominik","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aronsky Dominik","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008186542","display_name":"Fiszman Marcelo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fiszman Marcelo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5108452690","display_name":"H. J.","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haug Peter J.","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.45351335,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9921000003814697,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9921000003814697,"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/T10350","display_name":"Electronic Health Records Systems","score":0.954800009727478,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9495999813079834,"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/guideline","display_name":"Guideline","score":0.7891432046890259},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6591005325317383},{"id":"https://openalex.org/keywords/pneumonia","display_name":"Pneumonia","score":0.6019418239593506},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5124743580818176},{"id":"https://openalex.org/keywords/decision-support-system","display_name":"Decision support system","score":0.4826400876045227},{"id":"https://openalex.org/keywords/diagnostic-accuracy","display_name":"Diagnostic accuracy","score":0.4477868676185608},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.4457804560661316},{"id":"https://openalex.org/keywords/clinical-decision-support-system","display_name":"Clinical decision support system","score":0.4170454144477844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3832201361656189},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37218716740608215},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3385090231895447},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.16284438967704773},{"id":"https://openalex.org/keywords/pathology","display_name":"Pathology","score":0.10818129777908325}],"concepts":[{"id":"https://openalex.org/C2780182762","wikidata":"https://www.wikidata.org/wiki/Q1630279","display_name":"Guideline","level":2,"score":0.7891432046890259},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6591005325317383},{"id":"https://openalex.org/C2777914695","wikidata":"https://www.wikidata.org/wiki/Q12192","display_name":"Pneumonia","level":2,"score":0.6019418239593506},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5124743580818176},{"id":"https://openalex.org/C107327155","wikidata":"https://www.wikidata.org/wiki/Q330268","display_name":"Decision support system","level":2,"score":0.4826400876045227},{"id":"https://openalex.org/C3020132585","wikidata":"https://www.wikidata.org/wiki/Q2671652","display_name":"Diagnostic accuracy","level":2,"score":0.4477868676185608},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4457804560661316},{"id":"https://openalex.org/C63527458","wikidata":"https://www.wikidata.org/wiki/Q5133829","display_name":"Clinical decision support system","level":3,"score":0.4170454144477844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3832201361656189},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37218716740608215},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3385090231895447},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.16284438967704773},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.10818129777908325},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/978-1-60750-928-8-493","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-60750-928-8-493","pdf_url":null,"source":{"id":"https://openalex.org/S4210179765","display_name":"Studies in health technology and informatics","issn_l":"0926-9630","issn":["0926-9630","1879-8365"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Studies in Health Technology and Informatics","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2046929026","https://openalex.org/W2779278343","https://openalex.org/W1996434451","https://openalex.org/W1569026615","https://openalex.org/W2791725133","https://openalex.org/W2338117633","https://openalex.org/W2112831187","https://openalex.org/W2122149485","https://openalex.org/W4232131108","https://openalex.org/W2098044946"],"abstract_inverted_index":{"Background:":[0],"In":[1],"busy":[2],"clinical":[3],"settings,":[4],"physicians":[5],"often":[6],"do":[7],"not":[8,250],"have":[9,60],"enough":[10],"time":[11],"to":[12,40,76,258],"identify":[13,27],"patients":[14,29,58],"for":[15,34,56,65,154,175,185,193],"specific":[16,35],"therapeutic":[17],"guidelines.":[18],"As":[19],"a":[20,46,66,103,130,147,168,260],"solution,":[21],"decision":[22,85],"support":[23,86],"systems":[24],"could":[25],"automatically":[26],"eligible":[28,64],"and":[30,50,62,98,123,134,178,183,188,191,207],"trigger":[31],"computerized":[32],"guidelines":[33],"diseases.":[36],"Applying":[37],"this":[38,73],"idea":[39],"community-acquired":[41],"pneumonia":[42,67],"(CAP),":[43],"we":[44,113],"developed":[45],"Bayesian":[47],"network":[48,54],"(BN)":[49],"an":[51,199,211],"artificial":[52],"neural":[53],"(ANN)":[55],"identifying":[57,92],"who":[59],"CAP":[61,93],"are":[63,255],"guideline.":[68,261],"Objective:":[69],"The":[70,196,219,230],"aim":[71],"of":[72,82,91,106,132,149,170,201,213],"study":[74],"was":[75,224],"determine":[77],"whether":[78],"the":[79,100,116,118,124,137,140,158,161,172,186,194,208,222,237,242],"diagnostic":[80],"accuracy":[81],"these":[83],"two":[84],"models":[87],"differs":[88],"in":[89,244],"terms":[90],"patients.":[94,109],"Methods:":[95],"We":[96,152],"trained":[97],"tested":[99,153],"networks":[101,231,254],"with":[102],"data":[104,239],"set":[105],"32,662":[107],"adult":[108],"For":[110],"each":[111],"network,":[112],"(1)":[114],"calculated":[115],"specificity,":[117,176],"positive":[119],"predictive":[120,126],"value":[121,127],"(PPV),":[122],"negative":[125],"(NPV)":[128],"at":[129],"sensitivity":[131,169],"95%,":[133,171],"(2)":[135],"determined":[136],"area":[138,163],"under":[139],"receiver":[141],"operating":[142],"characteristic":[143],"curve":[144],"(AUC)":[145],"as":[146],"measure":[148],"overall":[150,234],"accuracy.":[151],"statistical":[155],"difference":[156,220,243],"between":[157,221],"AUCs":[159,223],"using":[160],"correlated":[162],"z":[164],"statistic.":[165],"Results:":[166],"At":[167],"respective":[173],"values":[174],"PPV,":[177],"NPV":[179],"were:":[180],"92.3%,":[181],"15.1%,":[182],"99.9%":[184,192],"BN,":[187],"94.0%,":[189],"18.6%,":[190],"ANN.":[195],"BN":[197],"had":[198,210],"AUC":[200,212],"0.9795":[202],"(95%":[203,215],"CI:":[204,216],"0.9736,":[205],"0.9843),":[206],"ANN":[209],"0.9855":[214],"0.9805,":[217],"0.9894).":[218],"statistically":[225,247],"significant":[226,248],"(p":[227],"=0.0044).":[228],"Conclusions:":[229],"achieved":[232],"high":[233],"accuracies":[235,245],"on":[236],"testing":[238],"set.":[240],"Because":[241],"is":[246],"but":[249],"clinically":[251],"significant,":[252],"both":[253],"equally":[256],"suited":[257],"drive":[259]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}