{"id":"https://openalex.org/W3216036741","doi":"https://doi.org/10.1093/jamia/ocab209","title":"Improving suicide risk prediction via targeted data fusion: proof of concept using medical claims data","display_name":"Improving suicide risk prediction via targeted data fusion: proof of concept using medical claims data","publication_year":2021,"publication_date":"2021-09-15","ids":{"openalex":"https://openalex.org/W3216036741","doi":"https://doi.org/10.1093/jamia/ocab209","mag":"3216036741","pmid":"https://pubmed.ncbi.nlm.nih.gov/34850890"},"language":"en","primary_location":{"id":"doi:10.1093/jamia/ocab209","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocab209","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8800522","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021858821","display_name":"Wanwan Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wanwan Xu","raw_affiliation_strings":["Department of Statistics, University of Connecticut, Storrs, Connecticut, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Connecticut, Storrs, Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102008930","display_name":"Chang Su","orcid":"https://orcid.org/0000-0003-4019-6389"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang Su","raw_affiliation_strings":["Department of Health Service Administration and Policy, Temple University, Philadelphia, Pennsylvania, USA"],"raw_orcid":"https://orcid.org/0000-0003-4019-6389","affiliations":[{"raw_affiliation_string":"Department of Health Service Administration and Policy, Temple University, Philadelphia, Pennsylvania, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380422","display_name":"Yan Li","orcid":"https://orcid.org/0000-0003-2182-9048"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Li","raw_affiliation_strings":["Department of Statistics, University of Connecticut, Storrs, Connecticut, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Connecticut, Storrs, Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064063695","display_name":"Steven C. Rogers","orcid":"https://orcid.org/0000-0002-8167-4191"},"institutions":[{"id":"https://openalex.org/I1302163369","display_name":"Hartford Hospital","ror":"https://ror.org/00gt5xe03","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1302163369"]},{"id":"https://openalex.org/I4210101648","display_name":"Connecticut Children's Medical Center","ror":"https://ror.org/01a1jjn24","country_code":"US","type":"funder","lineage":["https://openalex.org/I4210101648"]},{"id":"https://openalex.org/I75929689","display_name":"UConn Health","ror":"https://ror.org/02kzs4y22","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I75929689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steven Rogers","raw_affiliation_strings":["Department of Pediatrics, UCONN Health, Farmington, Connecticut, USA","Injury Prevention Center, Connecticut Children\u2019s and Hartford Hospital, Hartford, Connecticut, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Pediatrics, UCONN Health, Farmington, Connecticut, USA","institution_ids":["https://openalex.org/I75929689"]},{"raw_affiliation_string":"Injury Prevention Center, Connecticut Children\u2019s and Hartford Hospital, Hartford, Connecticut, USA","institution_ids":["https://openalex.org/I4210101648","https://openalex.org/I1302163369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100455768","display_name":"Fei Wang","orcid":"https://orcid.org/0000-0001-9459-9461"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Fei Wang","raw_affiliation_strings":["Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, New York, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100444485","display_name":"Kun Chen","orcid":"https://orcid.org/0000-0003-3579-5467"},"institutions":[{"id":"https://openalex.org/I140172145","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97","country_code":"US","type":"education","lineage":["https://openalex.org/I140172145"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kun Chen","raw_affiliation_strings":["Department of Statistics, University of Connecticut, Storrs, Connecticut, USA"],"raw_orcid":"https://orcid.org/0000-0003-3579-5467","affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Connecticut, Storrs, Connecticut, USA","institution_ids":["https://openalex.org/I140172145"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030001545","display_name":"Robert H. Aseltine","orcid":"https://orcid.org/0000-0003-3007-9867"},"institutions":[{"id":"https://openalex.org/I75929689","display_name":"UConn Health","ror":"https://ror.org/02kzs4y22","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I75929689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Aseltine","raw_affiliation_strings":["Division of Behavioral Sciences and Community Health, UConn Health, Farmington, Connecticut, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Behavioral Sciences and Community Health, UConn Health, Farmington, Connecticut, USA","institution_ids":["https://openalex.org/I75929689"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100455768"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":{"value":3967,"currency":"USD","value_usd":3967},"apc_paid":null,"fwci":1.6788,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.87301233,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"29","issue":"3","first_page":"500","last_page":"511"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13702","display_name":"Machine Learning in Healthcare","score":0.4560000002384186,"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":0.4560000002384186,"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/T10376","display_name":"Suicide and Self-Harm Studies","score":0.11129999905824661,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.03519999980926514,"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/predictive-modelling","display_name":"Predictive modelling","score":0.5292773842811584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5196781754493713},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.48931190371513367},{"id":"https://openalex.org/keywords/health-care","display_name":"Health care","score":0.4787677824497223},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.46077224612236023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4557277262210846},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4541548788547516},{"id":"https://openalex.org/keywords/linkage","display_name":"Linkage (software)","score":0.44387301802635193},{"id":"https://openalex.org/keywords/proof-of-concept","display_name":"Proof of concept","score":0.42205095291137695},{"id":"https://openalex.org/keywords/medical-record","display_name":"Medical record","score":0.4200674891471863},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41136372089385986},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.38452860713005066}],"concepts":[{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.5292773842811584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5196781754493713},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.48931190371513367},{"id":"https://openalex.org/C160735492","wikidata":"https://www.wikidata.org/wiki/Q31207","display_name":"Health care","level":2,"score":0.4787677824497223},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.46077224612236023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4557277262210846},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4541548788547516},{"id":"https://openalex.org/C31266012","wikidata":"https://www.wikidata.org/wiki/Q6554340","display_name":"Linkage (software)","level":3,"score":0.44387301802635193},{"id":"https://openalex.org/C124978682","wikidata":"https://www.wikidata.org/wiki/Q1201019","display_name":"Proof of concept","level":2,"score":0.42205095291137695},{"id":"https://openalex.org/C195910791","wikidata":"https://www.wikidata.org/wiki/Q1324077","display_name":"Medical record","level":2,"score":0.4200674891471863},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41136372089385986},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.38452860713005066},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D002648","descriptor_name":"Child","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003695","descriptor_name":"Delivery of Health Care","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":"D011237","descriptor_name":"Predictive Value of Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011237","descriptor_name":"Predictive Value of Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011237","descriptor_name":"Predictive Value of Tests","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012307","descriptor_name":"Risk Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012307","descriptor_name":"Risk Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012307","descriptor_name":"Risk Factors","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D013405","descriptor_name":"Suicide","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013405","descriptor_name":"Suicide","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D013405","descriptor_name":"Suicide","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D059020","descriptor_name":"Suicidal Ideation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D059020","descriptor_name":"Suicidal Ideation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D059020","descriptor_name":"Suicidal Ideation","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":3,"locations":[{"id":"doi:10.1093/jamia/ocab209","is_oa":false,"landing_page_url":"https://doi.org/10.1093/jamia/ocab209","pdf_url":null,"source":{"id":"https://openalex.org/S129839026","display_name":"Journal of the American Medical Informatics Association","issn_l":"1067-5027","issn":["1067-5027","1527-974X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the American Medical Informatics Association","raw_type":"journal-article"},{"id":"pmid:34850890","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34850890","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":"Journal of the American Medical Informatics Association : JAMIA","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:8800522","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8800522","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:pubmedcentral.nih.gov:8800522","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8800522","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,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Am Med Inform Assoc","raw_type":"Text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G1538084647","display_name":null,"funder_award_id":"R01MH112148","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"},{"id":"https://openalex.org/G6006632530","display_name":null,"funder_award_id":"R01MH124740","funder_id":"https://openalex.org/F4320332161","funder_display_name":"National Institutes of Health"}],"funders":[{"id":"https://openalex.org/F4320332161","display_name":"National Institutes of Health","ror":"https://ror.org/01cwqze88"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1965454346","https://openalex.org/W1985163828","https://openalex.org/W2012035409","https://openalex.org/W2024498794","https://openalex.org/W2033314834","https://openalex.org/W2041290212","https://openalex.org/W2050611336","https://openalex.org/W2106479238","https://openalex.org/W2123612404","https://openalex.org/W2132755184","https://openalex.org/W2165698076","https://openalex.org/W2509888018","https://openalex.org/W2557738935","https://openalex.org/W2581082771","https://openalex.org/W2611679938","https://openalex.org/W2750307043","https://openalex.org/W2788633781","https://openalex.org/W2799462250","https://openalex.org/W2801632865","https://openalex.org/W2806563890","https://openalex.org/W2921616123","https://openalex.org/W2944774301","https://openalex.org/W2982431490","https://openalex.org/W3008277872","https://openalex.org/W3016658072","https://openalex.org/W3023274595","https://openalex.org/W3087356181","https://openalex.org/W3109426378","https://openalex.org/W6774043905"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4224009465","https://openalex.org/W4286629047","https://openalex.org/W4306321456","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3160244858"],"abstract_inverted_index":{"OBJECTIVE:":[0],"Reducing":[1],"suicidal":[2],"behavior":[3],"among":[4],"patients":[5,78,122],"in":[6,79,123,148,232],"the":[7,109,124,149,161,175,180,190,227,240],"healthcare":[8,21,48,217],"system":[9],"requires":[10],"accurate":[11],"and":[12,113,126,134,166,172,174,186],"explainable":[13],"predictive":[14,177,212,230],"models":[15,231],"of":[16,70,229,239],"suicide":[17,104],"risk":[18,42,105,116,141],"across":[19],"diverse":[20],"settings.":[22],"MATERIALS":[23],"AND":[24,194],"METHODS:":[25],"We":[26,101,196],"proposed":[27,154,197],"a":[28,40,55,68,80,90,103,198,210],"general":[29,199],"targeted":[30,155,200],"fusion":[31,53,156,182,201],"learning":[32,202],"framework":[33,203],"that":[34,204],"can":[35,205,225],"be":[36,206],"used":[37,207],"to":[38,189,208],"build":[39,209],"tailored":[41,211],"prediction":[43,106],"model":[44,107,183,213],"for":[45,76,108,145,179,214],"any":[46,215],"specific":[47,216,233],"setting,":[49],"drawing":[50],"on":[51],"information":[52],"from":[54,98,220,243],"separate":[56],"more":[57,91],"comprehensive":[58,92],"dataset":[59,151],"with":[60,89],"indirect":[61],"sample":[62],"linkage":[63],"through":[64],"patient":[65,115,147],"similarities.":[66],"As":[67],"proof":[69],"concept,":[71],"we":[72,224],"predicted":[73],"suicide-related":[74],"hospitalizations":[75],"pediatric":[77],"limited":[81],"statewide":[82],"Hospital":[83],"Inpatient":[84],"Discharge":[85],"Dataset":[86],"(HIDD)":[87,128],"fused":[88,140],"medical":[93],"All-Payer":[94],"Claims":[95],"Database":[96],"(APCD)":[97,112],"Connecticut.":[99],"RESULTS:":[100],"built":[102],"source":[110,125],"data":[111,245],"calculated":[114],"scores.":[117],"Patient":[118],"similarity":[119],"scores":[120],"between":[121],"target":[127,150,234],"datasets":[129],"using":[130,152],"their":[131],"demographic":[132],"characteristics":[133],"diagnosis":[135],"codes":[136],"were":[137],"assessed.":[138],"A":[139],"score":[142],"was":[143],"generated":[144],"each":[146],"our":[153],"framework.":[157],"With":[158],"this":[159,221],"model,":[160],"averaged":[162],"sensitivities":[163],"at":[164],"90%":[165],"95%":[167],"specificity":[168],"improved":[169,184],"by":[170],"67%":[171],"171%,":[173],"positive":[176],"values":[178],"combined":[181],"64%":[185],"135%":[187],"compared":[188],"conventional":[191],"model.":[192],"DISCUSSION":[193],"CONCLUSIONS:":[195],"setting.":[218],"Results":[219],"study":[222],"suggest":[223],"improve":[226],"performance":[228],"settings":[235],"without":[236],"complete":[237],"integration":[238],"raw":[241],"records":[242],"external":[244],"sources.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-18T08:10:14.011955","created_date":"2025-10-10T00:00:00"}