{"id":"https://openalex.org/W3217565869","doi":"https://doi.org/10.1136/rmdopen-2021-001781","title":"Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis","display_name":"Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W3217565869","doi":"https://doi.org/10.1136/rmdopen-2021-001781","mag":"3217565869","pmid":"https://pubmed.ncbi.nlm.nih.gov/34819386","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/8614150"},"language":"en","primary_location":{"id":"doi:10.1136/rmdopen-2021-001781","doi":"https://doi.org/10.1136/rmdopen-2021-001781","is_oa":true,"landing_page_url":"https://doi.org/10.1136/rmdopen-2021-001781","pdf_url":"https://rmdopen.bmj.com/content/rmdopen/7/3/e001781.full.pdf","source":{"id":"https://openalex.org/S2738706341","display_name":"RMD Open","issn_l":"2056-5933","issn":["2056-5933"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319945","host_organization_name":"BMJ","host_organization_lineage":["https://openalex.org/P4310319945"],"host_organization_lineage_names":["BMJ"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"RMD Open","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://rmdopen.bmj.com/content/rmdopen/7/3/e001781.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002985352","display_name":"Alison K. Spencer","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alison K. Spencer","raw_affiliation_strings":["Data Science, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087202587","display_name":"Jigar N. Bandaria","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jigar Bandaria","raw_affiliation_strings":["Data Science, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066598954","display_name":"Michelle B Leavy","orcid":"https://orcid.org/0000-0003-1927-7248","observed_orcids":["https://orcid.org/0000-0003-1927-7248"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michelle B. Leavy","raw_affiliation_strings":["Research, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":"https://orcid.org/0000-0003-1927-7248","affiliations":[{"raw_affiliation_string":"Research, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060122899","display_name":"Benjamin Gliklich","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Benjamin Gliklich","raw_affiliation_strings":["Research, Noble and Greenough School, Dedham, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research, Noble and Greenough School, Dedham, Massachusetts, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015076603","display_name":"Zhaohui Su","orcid":"https://orcid.org/0000-0003-2005-9504","observed_orcids":["https://orcid.org/0000-0003-2005-9504"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaohui Su","raw_affiliation_strings":["Biostatistics, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Biostatistics, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051186379","display_name":"Gary C. Curhan","orcid":"https://orcid.org/0000-0001-7386-6305","observed_orcids":["https://orcid.org/0000-0001-7386-6305"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gary Curhan","raw_affiliation_strings":["Research, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016457559","display_name":"Costas Boussios","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Costas Boussios","raw_affiliation_strings":["Data Science, OM1 Inc, Boston, Massachusetts, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science, OM1 Inc, Boston, Massachusetts, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5066598954"],"corresponding_institution_ids":[],"apc_list":{"value":1950,"currency":"GBP","value_usd":2391},"apc_paid":{"value":1950,"currency":"GBP","value_usd":2391},"fwci":0.4395,"has_fulltext":true,"cited_by_count":11,"citation_normalized_percentile":{"value":0.64400416,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"7","issue":"3","first_page":"e001781","last_page":"e001781"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.9208999872207642,"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":0.9208999872207642,"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/T10200","display_name":"Rheumatoid Arthritis Research and Therapies","score":0.04320000112056732,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.009200000204145908,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/rheumatoid-arthritis","display_name":"rheumatoid arthritis","score":0.984000027179718},{"id":"https://openalex.org/keywords/clinical-disease-activity-index","display_name":"Clinical Disease Activity Index","score":0.9909999966621399},{"id":"https://openalex.org/keywords/clinical-notes","display_name":"clinical notes","score":0.8650000095367432},{"id":"https://openalex.org/keywords/electronic-health-records","display_name":"electronic health records","score":0.6600000262260437},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"natural language processing","score":0.796999990940094},{"id":"https://openalex.org/keywords/disease-activity-assessment","display_name":"disease activity assessment","score":0.5649999976158142},{"id":"https://openalex.org/keywords/real-world-data","display_name":"real-world data","score":0.9110000133514404},{"id":"https://openalex.org/keywords/model-validation","display_name":"model validation","score":0.5540000200271606}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.92962646484375},{"id":"https://openalex.org/C2777575956","wikidata":"https://www.wikidata.org/wiki/Q187255","display_name":"Rheumatoid arthritis","level":2,"score":0.6706864237785339},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.6438564658164978},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.6400606036186218},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.5412077903747559},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.5213881134986877},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.48916366696357727},{"id":"https://openalex.org/C198451711","wikidata":"https://www.wikidata.org/wiki/Q327657","display_name":"Rheumatology","level":2,"score":0.45659339427948},{"id":"https://openalex.org/C2992264114","wikidata":"https://www.wikidata.org/wiki/Q1394551","display_name":"Clinical disease","level":3,"score":0.41938716173171997},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40994611382484436},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.31311899423599243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.0}],"mesh":[{"descriptor_ui":"D000069550","descriptor_name":"Machine Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001172","descriptor_name":"Arthritis, Rheumatoid","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012219","descriptor_name":"Rheumatology","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012720","descriptor_name":"Severity of Illness Index","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D015331","descriptor_name":"Cohort Studies","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":4,"locations":[{"id":"doi:10.1136/rmdopen-2021-001781","doi":"https://doi.org/10.1136/rmdopen-2021-001781","is_oa":true,"landing_page_url":"https://doi.org/10.1136/rmdopen-2021-001781","pdf_url":"https://rmdopen.bmj.com/content/rmdopen/7/3/e001781.full.pdf","source":{"id":"https://openalex.org/S2738706341","display_name":"RMD Open","issn_l":"2056-5933","issn":["2056-5933"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319945","host_organization_name":"BMJ","host_organization_lineage":["https://openalex.org/P4310319945"],"host_organization_lineage_names":["BMJ"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"RMD Open","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8614150","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8614150","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,"listed_in":[],"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":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"RMD Open","raw_type":"Text"},{"id":"pmid:34819386","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34819386","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,"listed_in":[],"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":"RMD open","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:ff7c5d72970048d49736fc6b49aa280f","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/ff7c5d72970048d49736fc6b49aa280f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"RMD Open, Vol 7, Iss 3 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1136/rmdopen-2021-001781","doi":"https://doi.org/10.1136/rmdopen-2021-001781","is_oa":true,"landing_page_url":"https://doi.org/10.1136/rmdopen-2021-001781","pdf_url":"https://rmdopen.bmj.com/content/rmdopen/7/3/e001781.full.pdf","source":{"id":"https://openalex.org/S2738706341","display_name":"RMD Open","issn_l":"2056-5933","issn":["2056-5933"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","doyens","jufo-1","ki-jl-1","medline","norway-1","oarl","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319945","host_organization_name":"BMJ","host_organization_lineage":["https://openalex.org/P4310319945"],"host_organization_lineage_names":["BMJ"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"RMD Open","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.9537000060081482,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3217565869.pdf","grobid_xml":"https://content.openalex.org/works/W3217565869.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1761300068","https://openalex.org/W2098919737","https://openalex.org/W2121399461","https://openalex.org/W2126525702","https://openalex.org/W2162539122","https://openalex.org/W2165724007","https://openalex.org/W2914827023","https://openalex.org/W2921861522","https://openalex.org/W2988345887","https://openalex.org/W2990706997","https://openalex.org/W3007915134","https://openalex.org/W3162370127"],"related_works":["https://openalex.org/W4310358385","https://openalex.org/W4416388366","https://openalex.org/W7154172220","https://openalex.org/W4413122633","https://openalex.org/W3109848919","https://openalex.org/W2736393579","https://openalex.org/W4304471423","https://openalex.org/W2038672216","https://openalex.org/W2150571985","https://openalex.org/W4225643534"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Disease":[1,8],"activity":[2],"measures,":[3],"such":[4],"as":[5],"the":[6,97,148,151,172,203,207,229,250],"Clinical":[7],"Activity":[9],"Index":[10],"(CDAI),":[11],"are":[12],"important":[13],"tools":[14],"for":[15,50,68,264],"informing":[16],"treatment":[17],"decisions":[18],"and":[19,36,112,139,161,177,195,218],"monitoring":[20],"patient":[21],"outcomes":[22],"in":[23,32],"rheumatoid":[24],"arthritis":[25],"(RA).":[26],"Yet,":[27],"documentation":[28],"of":[29,54,108,117,123,171,190,193,197,206,216,223,249],"CDAI":[30,66,84,137,231,240,259],"scores":[31,67,241,260],"electronic":[33],"medical":[34],"records":[35],"other":[37],"real-world":[38,253],"data":[39,49,254],"sources":[40],"is":[41],"inconsistent,":[42],"making":[43],"it":[44],"challenging":[45],"to":[46,58,64,82,103,252,261],"use":[47],"these":[48],"research.":[51],"The":[52,174,185,209],"purpose":[53],"this":[55],"study":[56],"was":[57,80,145],"validate":[59],"a":[60,91,105,113,126,135,140,168,188,212,219],"machine":[61,77,236],"learning":[62,78,237],"model":[63,79,186,210,238,251],"estimate":[65,83],"patients":[69],"with":[70,245],"RA":[71,99],"using":[72,87,147,167,202,228],"clinical":[73,88,141,243],"notes.":[74],"METHODS:":[75],"A":[76,235],"developed":[81],"score":[85,138],"values":[86,180],"notes":[89,244],"from":[90,96,242],"specific":[92],"rheumatology":[93],"visit.":[94],"Data":[95],"OM1":[98],"Registry":[100],"were":[101,181],"used":[102,263],"create":[104],"training":[106],"cohort":[107,116],"56":[109],"177":[110],"encounters":[111,132],"separate":[114],"validation":[115],"18":[118],"726":[119],"encounters,":[120],"11":[121],"985":[122],"which":[124],"passed":[125],"model-derived":[127],"confidence":[128],"filter;":[129],"all":[130],"included":[131],"had":[133,187,211],"both":[134],"clinician-recorded":[136],"note.":[142],"Model":[143],"performance":[144,201,227],"assessed":[146],"area":[149],"under":[150],"receiver":[152],"operating":[153],"characteristic":[154],"curve":[155],"(AUC),":[156],"positive":[157],"predictive":[158,163],"value":[159,164,215,222],"(PPV)":[160],"negative":[162],"(NPV),":[165],"calculated":[166],"binarised":[169,204],"version":[170,205],"outcome.":[173,208],"Spearman's":[175,213],"R":[176,179,214,221],"Pearson's":[178,220],"also":[182],"calculated.":[183],"RESULTS:":[184],"PPV":[189],"0.80,":[191],"NPV":[192],"0.84":[194],"AUC":[196],"0.88":[198],"when":[199,225],"evaluating":[200,226],"0.72":[217],"0.69":[224],"continuous":[230],"numeric":[232],"scores.":[233],"CONCLUSION:":[234],"estimates":[239],"good":[246],"performance.":[247],"Application":[248],"sets":[255],"may":[256],"allow":[257],"estimated":[258],"be":[262],"research":[265],"purposes.":[266]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2026-10-31T12:09:11.096373","created_date":"2021-12-06T00:00:00"}
