{"id":"https://openalex.org/W2055600764","doi":"https://doi.org/10.1145/1882992.1883062","title":"A data mining approach to MPGN type II renal survival analysis","display_name":"A data mining approach to MPGN type II renal survival analysis","publication_year":2010,"publication_date":"2010-11-11","ids":{"openalex":"https://openalex.org/W2055600764","doi":"https://doi.org/10.1145/1882992.1883062","mag":"2055600764"},"language":"en","primary_location":{"id":"doi:10.1145/1882992.1883062","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1882992.1883062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM International Health Informatics Symposium","raw_type":"proceedings-article"},"type":"article","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":"https://openalex.org/A5100350493","display_name":"Yang Chen","orcid":"https://orcid.org/0000-0003-3689-2680"},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chen Yang","raw_affiliation_strings":["The University of Iowa, Iowa City, IA, USA",", The University of Iowa, Iowa City, IA, USA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":", The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103532586","display_name":"Nick W. Street","orcid":null},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nick W. Street","raw_affiliation_strings":["The University of Iowa, Iowa City, IA, USA",", The University of Iowa, Iowa City, IA, USA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":", The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082092206","display_name":"Der-Fa Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Der-Fa Lu","raw_affiliation_strings":["The University of Iowa, Iowa City, IA, USA",", The University of Iowa, Iowa City, IA, USA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":", The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004592436","display_name":"Lynne D. Lanning","orcid":null},"institutions":[{"id":"https://openalex.org/I126307644","display_name":"University of Iowa","ror":"https://ror.org/036jqmy94","country_code":"US","type":"education","lineage":["https://openalex.org/I126307644"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lynne Lanning","raw_affiliation_strings":["The University of Iowa, Iowa City, IA, USA",", The University of Iowa, Iowa City, IA, USA"],"affiliations":[{"raw_affiliation_string":"The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]},{"raw_affiliation_string":", The University of Iowa, Iowa City, IA, USA","institution_ids":["https://openalex.org/I126307644"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100350493"],"corresponding_institution_ids":["https://openalex.org/I126307644"],"apc_list":null,"apc_paid":null,"fwci":0.4765,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.64807367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"454","last_page":"458"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11029","display_name":"Renal Diseases and Glomerulopathies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"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/T11029","display_name":"Renal Diseases and Glomerulopathies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2727","display_name":"Nephrology"},"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/T10697","display_name":"Vasculitis and related conditions","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/2740","display_name":"Pulmonary and Respiratory Medicine"},"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/T10308","display_name":"Systemic Lupus Erythematosus Research","score":0.9951000213623047,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7026869058609009},{"id":"https://openalex.org/keywords/proportional-hazards-model","display_name":"Proportional hazards model","score":0.696579098701477},{"id":"https://openalex.org/keywords/disease","display_name":"Disease","score":0.6060609221458435},{"id":"https://openalex.org/keywords/membranoproliferative-glomerulonephritis","display_name":"Membranoproliferative glomerulonephritis","score":0.5037125945091248},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.48771724104881287},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4474124312400818},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4353521764278412},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.41064178943634033},{"id":"https://openalex.org/keywords/oncology","display_name":"Oncology","score":0.32345086336135864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3002500534057617},{"id":"https://openalex.org/keywords/glomerulonephritis","display_name":"Glomerulonephritis","score":0.1706606149673462},{"id":"https://openalex.org/keywords/kidney","display_name":"Kidney","score":0.10125604271888733}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7026869058609009},{"id":"https://openalex.org/C50382708","wikidata":"https://www.wikidata.org/wiki/Q223218","display_name":"Proportional hazards model","level":2,"score":0.696579098701477},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.6060609221458435},{"id":"https://openalex.org/C2781036514","wikidata":"https://www.wikidata.org/wiki/Q2299379","display_name":"Membranoproliferative glomerulonephritis","level":4,"score":0.5037125945091248},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.48771724104881287},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4474124312400818},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4353521764278412},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.41064178943634033},{"id":"https://openalex.org/C143998085","wikidata":"https://www.wikidata.org/wiki/Q162555","display_name":"Oncology","level":1,"score":0.32345086336135864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3002500534057617},{"id":"https://openalex.org/C2780368995","wikidata":"https://www.wikidata.org/wiki/Q605006","display_name":"Glomerulonephritis","level":3,"score":0.1706606149673462},{"id":"https://openalex.org/C2780091579","wikidata":"https://www.wikidata.org/wiki/Q9377","display_name":"Kidney","level":2,"score":0.10125604271888733}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1882992.1883062","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1882992.1883062","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st ACM International Health Informatics Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W740415","https://openalex.org/W44024118","https://openalex.org/W415308873","https://openalex.org/W1534555782","https://openalex.org/W1580788756","https://openalex.org/W2023643044","https://openalex.org/W2120618976","https://openalex.org/W2153635508","https://openalex.org/W2156909104","https://openalex.org/W2157133617","https://openalex.org/W3120421331","https://openalex.org/W3147894994","https://openalex.org/W4296154464"],"related_works":["https://openalex.org/W1522417257","https://openalex.org/W1554478097","https://openalex.org/W190230789","https://openalex.org/W2461402705","https://openalex.org/W24257972","https://openalex.org/W2182576916","https://openalex.org/W2048415999","https://openalex.org/W599250499","https://openalex.org/W4327962982","https://openalex.org/W1992015621"],"abstract_inverted_index":{"There":[0],"are":[1],"three":[2],"recognized":[3],"types":[4],"of":[5,19,26,37,50,74],"Membranoproliferative":[6],"glomerulonephritis":[7],"(MPGN).":[8],"Type":[9],"II":[10],"or":[11],"Dense":[12],"Deposit":[13],"Disease":[14],"(DDD)has":[15],"a":[16,66,98,107],"renal":[17,39],"survival":[18,148],"50%":[20],"at":[21,34],"10":[22],"years.":[23],"The":[24],"goal":[25],"this":[27],"study":[28],"was":[29],"to":[30,41,47,65,87,146,156],"better":[31],"identify":[32],"patients":[33,62,160],"high":[35],"risk":[36],"early":[38],"failure,and":[40],"understand":[42],"the":[43,51,59,71,85,111,116,125,130],"factors":[44],"that":[45],"lead":[46],"fast":[48,139],"progression":[49],"disease.":[52],"We":[53,82],"identified":[54],"six":[55],"diagnostic":[56],"features":[57,76,86,120],"on":[58],"98":[60],"DDD":[61],"who":[63],"responed":[64],"Web-based":[67],"survey,":[68],"and":[69,79,102,118,150,152,159],"examined":[70],"prognostic":[72,123],"performance":[73],"these":[75],"in":[77,135,161],"isolation":[78],"simple":[80],"combinations.":[81],"then":[83],"combined":[84,126],"build":[88],"predictive":[89],"models":[90,127],"using":[91],"both":[92],"Cox":[93],"proportional":[94],"hazards":[95],"regression":[96],"(CHR),":[97],"standard":[99],"statistical":[100],"approach,":[101],"support":[103],"vector":[104],"machines":[105],"(SVMs),":[106],"classification":[108],"technique":[109],"from":[110],"data":[112],"mining":[113],"literature.":[114],"While":[115],"age":[117],"gender":[119],"showed":[121],"some":[122],"ability,":[124],"--":[128,132],"particularly":[129],"SVM":[131],"were":[133],"superior":[134],"identifying":[136],"cases":[137],"with":[138],"disease":[140,147],"progression.This":[141],"approach":[142],"can":[143],"be":[144,154],"applied":[145],"analysis":[149],"prognosis,":[151],"might":[153],"useful":[155],"healthcare":[157,163],"providers":[158],"making":[162],"decisions.":[164]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}