{"id":"https://openalex.org/W2408406473","doi":"https://doi.org/10.1109/icassp.2016.7472122","title":"Gold classification of COPDGene cohort based on deep learning","display_name":"Gold classification of COPDGene cohort based on deep learning","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2408406473","doi":"https://doi.org/10.1109/icassp.2016.7472122","mag":"2408406473"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103063055","display_name":"Jun Ying","orcid":"https://orcid.org/0000-0002-7693-4243"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]},{"id":"https://openalex.org/I4210103679","display_name":"Beijing Emergency Medical Center","ror":"https://ror.org/018zkg706","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210103679"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jun Ying","raw_affiliation_strings":["Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","Medical Support Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I4210087915"]},{"raw_affiliation_string":"Medical Support Center, Beijing, China","institution_ids":["https://openalex.org/I4210103679"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049372409","display_name":"Joyita Dutta","orcid":"https://orcid.org/0000-0002-6712-4927"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joyita Dutta","raw_affiliation_strings":["Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I4210087915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100679378","display_name":"Ning Guo","orcid":"https://orcid.org/0000-0002-8432-7056"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ning Guo","raw_affiliation_strings":["Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I4210087915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112389574","display_name":"Lei Xia","orcid":"https://orcid.org/0009-0001-1201-6064"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Xia","raw_affiliation_strings":["Medical Support Center, 301 Hospital, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Medical Support Center, 301 Hospital, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080126237","display_name":"Arkadiusz Sitek","orcid":"https://orcid.org/0000-0002-0677-4002"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arkadiusz Sitek","raw_affiliation_strings":["Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I4210087915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058429770","display_name":"Quanzheng Li","orcid":"https://orcid.org/0000-0002-9651-5820"},"institutions":[{"id":"https://openalex.org/I4210087915","display_name":"Massachusetts General Hospital","ror":"https://ror.org/002pd6e78","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210087915","https://openalex.org/I48633490"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Quanzheng Li","raw_affiliation_strings":["Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nuclear Medicine and Molecular Imaging Radiology Department, Massachusetts General Hospital, Boston, MA, USA","institution_ids":["https://openalex.org/I4210087915"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2474","last_page":"2478"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10143","display_name":"Chronic Obstructive Pulmonary Disease (COPD) Research","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10143","display_name":"Chronic Obstructive Pulmonary Disease (COPD) Research","score":0.9993000030517578,"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/T12419","display_name":"Phonocardiography and Auscultation Techniques","score":0.9711999893188477,"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/T14374","display_name":"Statistical Methods in Epidemiology","score":0.9003000259399414,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7431161403656006},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7065893411636353},{"id":"https://openalex.org/keywords/exacerbation","display_name":"Exacerbation","score":0.698754608631134},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.641967236995697},{"id":"https://openalex.org/keywords/cohort","display_name":"Cohort","score":0.5948121547698975},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5933531522750854},{"id":"https://openalex.org/keywords/copd","display_name":"COPD","score":0.5446053147315979},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5334653258323669},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.513400673866272},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5095577239990234},{"id":"https://openalex.org/keywords/gold-standard","display_name":"Gold standard (test)","score":0.4596173167228699},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.43283557891845703},{"id":"https://openalex.org/keywords/pulmonary-disease","display_name":"Pulmonary disease","score":0.42844170331954956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4155791997909546},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36857569217681885},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.2989552617073059}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7431161403656006},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7065893411636353},{"id":"https://openalex.org/C2777014857","wikidata":"https://www.wikidata.org/wiki/Q1383410","display_name":"Exacerbation","level":2,"score":0.698754608631134},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.641967236995697},{"id":"https://openalex.org/C72563966","wikidata":"https://www.wikidata.org/wiki/Q1303415","display_name":"Cohort","level":2,"score":0.5948121547698975},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5933531522750854},{"id":"https://openalex.org/C2776780178","wikidata":"https://www.wikidata.org/wiki/Q199804","display_name":"COPD","level":2,"score":0.5446053147315979},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5334653258323669},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.513400673866272},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5095577239990234},{"id":"https://openalex.org/C40993552","wikidata":"https://www.wikidata.org/wiki/Q514654","display_name":"Gold standard (test)","level":2,"score":0.4596173167228699},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.43283557891845703},{"id":"https://openalex.org/C2992779976","wikidata":"https://www.wikidata.org/wiki/Q3286546","display_name":"Pulmonary disease","level":2,"score":0.42844170331954956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4155791997909546},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36857569217681885},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.2989552617073059},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472122","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472122","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":24,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W1538101407","https://openalex.org/W1975962029","https://openalex.org/W2002726093","https://openalex.org/W2082907106","https://openalex.org/W2106051978","https://openalex.org/W2110429964","https://openalex.org/W2110798204","https://openalex.org/W2120432001","https://openalex.org/W2124478449","https://openalex.org/W2128873747","https://openalex.org/W2130230386","https://openalex.org/W2131579020","https://openalex.org/W2135074746","https://openalex.org/W2136922672","https://openalex.org/W2141778357","https://openalex.org/W2147004616","https://openalex.org/W2152904301","https://openalex.org/W2799061466","https://openalex.org/W4302161581","https://openalex.org/W6600949241","https://openalex.org/W6632120347","https://openalex.org/W6676481782","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W1992577796","https://openalex.org/W4309103225","https://openalex.org/W2130939671","https://openalex.org/W2110265450","https://openalex.org/W4311699418","https://openalex.org/W2952884403","https://openalex.org/W2130829219","https://openalex.org/W2801381949","https://openalex.org/W2906214541","https://openalex.org/W2924279227"],"abstract_inverted_index":{"This":[0],"study":[1],"aims":[2],"to":[3,41],"employ":[4],"deep":[5,27],"learning":[6],"for":[7,14,45,135,139],"the":[8,15,48,57,63,76,84,107,113,129],"development":[9],"of":[10,17,91],"an":[11,89],"automatic":[12],"classifier":[13],"severity":[16],"chronic":[18],"obstructive":[19],"pulmonary":[20],"disease":[21],"(COPD)":[22],"in":[23,75],"patients.":[24],"A":[25],"three-layer":[26],"belief":[28],"network":[29],"(DBN)":[30],"with":[31,69,112],"two":[32],"hidden":[33],"layers":[34],"and":[35,47,81,120],"one":[36],"visible":[37],"layer":[38],"was":[39,53],"employed":[40],"generate":[42],"a":[43,95,132],"model":[44],"classification,":[46],"model's":[49],"robustness":[50],"against":[51],"exacerbation":[52,136],"analyzed.":[54],"Subjects":[55],"from":[56],"COPDGene":[58],"cohort":[59],"were":[60,73,110],"staged":[61],"using":[62,94],"GOLD":[64],"2011":[65],"guidelines.":[66],"10,300":[67],"subjects":[68],"361":[70],"features":[71,103],"each":[72],"included":[74],"analysis.":[77],"After":[78],"feature":[79],"selection":[80],"parameter":[82],"optimization,":[83],"proposed":[85],"classification":[86],"method":[87],"achieved":[88],"accuracy":[90],"97.2%":[92],"by":[93,106],"10-fold":[96],"cross":[97],"validation":[98],"experiment.":[99],"The":[100],"most":[101],"sensitive":[102],"as":[104,116],"revealed":[105],"DBN":[108,130],"weights":[109],"consistent":[111],"clinical":[114,121],"consensus":[115],"per":[117],"previous":[118],"studies":[119],"diagnosis":[122],"rules.":[123],"In":[124],"summary,":[125],"we":[126],"demonstrate":[127],"that":[128],"is":[131],"competitive":[133],"tool":[134],"risk":[137],"assessment":[138],"patients":[140],"suffering":[141],"from,":[142],"COPD.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
