{"id":"https://openalex.org/W2006726681","doi":"https://doi.org/10.3390/e16073866","title":"Many Can Work Better than the Best: Diagnosing with Medical Images via Crowdsourcing","display_name":"Many Can Work Better than the Best: Diagnosing with Medical Images via Crowdsourcing","publication_year":2014,"publication_date":"2014-07-14","ids":{"openalex":"https://openalex.org/W2006726681","doi":"https://doi.org/10.3390/e16073866","mag":"2006726681"},"language":"en","primary_location":{"id":"doi:10.3390/e16073866","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e16073866","pdf_url":"https://www.mdpi.com/1099-4300/16/7/3866/pdf?version=1424785609","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1099-4300/16/7/3866/pdf?version=1424785609","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104043660","display_name":"Xianhong Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210128921","display_name":"The First Affiliated Hospital, Sun Yat-sen University","ror":"https://ror.org/037p24858","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian-Hong Xiang","raw_affiliation_strings":["Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China","institution_ids":["https://openalex.org/I4210128921","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101588489","display_name":"Xiaoyu Huang","orcid":"https://orcid.org/0000-0002-6696-4203"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Yu Huang","raw_affiliation_strings":["School of Economics and Commerce, South China University of Technology, Guangzhou 510006, China","Software Institute, Sun Yat-Sen University, Guangzhou 510275, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Economics and Commerce, South China University of Technology, Guangzhou 510006, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Software Institute, Sun Yat-Sen University, Guangzhou 510275, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100385986","display_name":"Xiaoling Zhang","orcid":"https://orcid.org/0000-0002-6369-9424"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210128921","display_name":"The First Affiliated Hospital, Sun Yat-sen University","ror":"https://ror.org/037p24858","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao-Ling Zhang","raw_affiliation_strings":["Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China","institution_ids":["https://openalex.org/I4210128921","https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Chun-Fang Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210105982","display_name":"Guangzhou Women and Children Medical Center","ror":"https://ror.org/01g53at17","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210105982"]},{"id":"https://openalex.org/I92039509","display_name":"Guangzhou Medical University","ror":"https://ror.org/00zat6v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I92039509"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun-Fang Cai","raw_affiliation_strings":["Department of Gynaecology and Obstetrics, Guangzhou Women and Children Medical Center, Guangzhou 510623, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Gynaecology and Obstetrics, Guangzhou Women and Children Medical Center, Guangzhou 510623, China","institution_ids":["https://openalex.org/I92039509","https://openalex.org/I4210105982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028798780","display_name":"Jianyong Yang","orcid":"https://orcid.org/0000-0001-6767-9351"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]},{"id":"https://openalex.org/I4210128921","display_name":"The First Affiliated Hospital, Sun Yat-sen University","ror":"https://ror.org/037p24858","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210128921"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian-Yong Yang","raw_affiliation_strings":["Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Interventional Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510080, China","institution_ids":["https://openalex.org/I4210128921","https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440326","display_name":"Lei Li","orcid":"https://orcid.org/0000-0002-5374-7293"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["Software Institute, Sun Yat-Sen University, Guangzhou 510275, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Software Institute, Sun Yat-Sen University, Guangzhou 510275, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5028798780"],"corresponding_institution_ids":["https://openalex.org/I157773358","https://openalex.org/I4210128921"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.4546,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.76597912,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"16","issue":"7","first_page":"3866","last_page":"3877"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12422","display_name":"Radiomics and Machine Learning in Medical Imaging","score":0.9713000059127808,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"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/crowdsourcing","display_name":"Crowdsourcing","score":0.9645910263061523},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.700905442237854},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6794674396514893},{"id":"https://openalex.org/keywords/judgement","display_name":"Judgement","score":0.6747044920921326},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6538790464401245},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5162701606750488},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5122076869010925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4792485237121582},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4775310754776001},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3859323263168335},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08204430341720581},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08033716678619385}],"concepts":[{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.9645910263061523},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.700905442237854},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6794674396514893},{"id":"https://openalex.org/C2776548248","wikidata":"https://www.wikidata.org/wiki/Q12621536","display_name":"Judgement","level":2,"score":0.6747044920921326},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6538790464401245},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5162701606750488},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5122076869010925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4792485237121582},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4775310754776001},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3859323263168335},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08204430341720581},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08033716678619385},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/e16073866","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e16073866","pdf_url":"https://www.mdpi.com/1099-4300/16/7/3866/pdf?version=1424785609","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:570747f09d4e40489feebd76d895e822","is_oa":true,"landing_page_url":"https://doaj.org/article/570747f09d4e40489feebd76d895e822","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,"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":"Entropy, Vol 16, Iss 7, Pp 3866-3877 (2014)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/e16073866","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e16073866","pdf_url":"https://www.mdpi.com/1099-4300/16/7/3866/pdf?version=1424785609","source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320326279","display_name":"Department of Education of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335795","display_name":"Science and Technology Planning Project of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320336024","display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2006726681.pdf","grobid_xml":"https://content.openalex.org/works/W2006726681.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1576013900","https://openalex.org/W1590411898","https://openalex.org/W1784474692","https://openalex.org/W1969031137","https://openalex.org/W1970381522","https://openalex.org/W1987406389","https://openalex.org/W2010483204","https://openalex.org/W2022710553","https://openalex.org/W2091051760","https://openalex.org/W2099111195","https://openalex.org/W2109411133","https://openalex.org/W2112193291","https://openalex.org/W2119110768","https://openalex.org/W2119679202","https://openalex.org/W2141282920","https://openalex.org/W2164124780","https://openalex.org/W2341535507","https://openalex.org/W2467426667","https://openalex.org/W6703949738"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W1503094549","https://openalex.org/W4384486036","https://openalex.org/W135177976","https://openalex.org/W2337920774","https://openalex.org/W4318823662","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W3207526114","https://openalex.org/W2503032459"],"abstract_inverted_index":{"We":[0],"study":[1],"a":[2],"crowdsourcing-based":[3],"diagnosis":[4,60,78],"algorithm,":[5],"which":[6],"is":[7,25,70],"against":[8],"the":[9,30,58,64,73,77,82,90,95,101],"fact":[10],"that":[11,98],"currently":[12],"we":[13,43,56,85],"do":[14],"not":[15],"lack":[16],"medical":[17],"staff,":[18],"but":[19],"high":[20],"level":[21],"experts.":[22],"Our":[23,67],"approach":[24],"to":[26,47,62],"make":[27],"use":[28],"of":[29,76],"general":[31],"practitioners\u2019":[32],"efforts:":[33],"For":[34],"every":[35],"patient":[36],"whose":[37],"illness":[38],"cannot":[39],"be":[40,48],"judged":[41],"definitely,":[42],"arrange":[44],"for":[45],"them":[46],"diagnosed":[49],"multiple":[50],"times":[51],"by":[52],"different":[53],"doctors,":[54],"and":[55,92],"collect":[57],"all":[59],"results":[61,96],"derive":[63],"final":[65],"judgement.":[66],"inference":[68],"model":[69],"based":[71],"on":[72,88],"statistical":[74],"consistency":[75],"data.":[79],"To":[80],"evaluate":[81],"proposed":[83],"model,":[84],"conduct":[86],"experiments":[87],"both":[89],"synthetic":[91],"real":[93],"data;":[94],"show":[97],"it":[99],"outperforms":[100],"benchmarks.":[102]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}