{"id":"https://openalex.org/W2129456158","doi":"https://doi.org/10.1186/1472-6882-12-127","title":"Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines","display_name":"Computer-assisted lip diagnosis on traditional Chinese medicine using multi-class support vector machines","publication_year":2012,"publication_date":"2012-08-16","ids":{"openalex":"https://openalex.org/W2129456158","doi":"https://doi.org/10.1186/1472-6882-12-127","mag":"2129456158","pmid":"https://pubmed.ncbi.nlm.nih.gov/22898352"},"language":"en","primary_location":{"id":"doi:10.1186/1472-6882-12-127","doi":"https://doi.org/10.1186/1472-6882-12-127","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1472-6882-12-127","pdf_url":"https://bmccomplementmedtherapies.biomedcentral.com/counter/pdf/10.1186/1472-6882-12-127","source":{"id":"https://openalex.org/S163220592","display_name":"BMC Complementary and Alternative Medicine","issn_l":"1472-6882","issn":["1472-6882"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","ki-jl-1","poland-100","vabb-shw"],"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Complementary and Alternative Medicine","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://bmccomplementmedtherapies.biomedcentral.com/counter/pdf/10.1186/1472-6882-12-127","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032768475","display_name":"Fufeng Li","orcid":"https://orcid.org/0000-0002-0566-3589","observed_orcids":["https://orcid.org/0000-0002-0566-3589"]},"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"]},{"id":"https://openalex.org/I4210098460","display_name":"Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/00z27jk27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210098460"]},{"id":"https://openalex.org/I4405286254","display_name":"Houston Methodist Research Institute","ror":"https://ror.org/01mcrxx35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295876152","https://openalex.org/I4405286254"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"FuFeng Li","raw_affiliation_strings":["Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China. fufeng_lee@hotmail.com","Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA","Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China. fufeng_lee@hotmail.com","institution_ids":["https://openalex.org/I4210098460"]},{"raw_affiliation_string":"Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405286254"]},{"raw_affiliation_string":"Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210098460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061497411","display_name":"Changbo Zhao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changbo Zhao","raw_affiliation_strings":["Department of Control Science & Engineering, Tongji University, Shanghai, China","Dept.of Control Science and Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Science & Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"Dept.of Control Science and Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zheng Xia","orcid":null,"observed_orcids":[]},"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"]},{"id":"https://openalex.org/I4405286254","display_name":"Houston Methodist Research Institute","ror":"https://ror.org/01mcrxx35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295876152","https://openalex.org/I4405286254"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zheng Xia","raw_affiliation_strings":["Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405286254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100662109","display_name":"Yiqin Wang","orcid":"https://orcid.org/0000-0002-0280-7495","observed_orcids":["https://orcid.org/0000-0002-0280-7495"]},"institutions":[{"id":"https://openalex.org/I4210098460","display_name":"Shanghai University of Traditional Chinese Medicine","ror":"https://ror.org/00z27jk27","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210098460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqin Wang","raw_affiliation_strings":["Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, China","Laboratory of Information Access and Synthesis of TCM Four Diagnosis Shanghai University of Traditional Chinese Medicine, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Information Access and Synthesis of TCM Four Diagnosis, Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210098460"]},{"raw_affiliation_string":"Laboratory of Information Access and Synthesis of TCM Four Diagnosis Shanghai University of Traditional Chinese Medicine, Shanghai, China","institution_ids":["https://openalex.org/I4210098460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040883232","display_name":"Xiaobo Zhou","orcid":"https://orcid.org/0000-0001-7191-6495","observed_orcids":["https://orcid.org/0000-0001-7191-6495","https://orcid.org/0000-0002-5895-0127"]},"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"]},{"id":"https://openalex.org/I4405286254","display_name":"Houston Methodist Research Institute","ror":"https://ror.org/01mcrxx35","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I1295876152","https://openalex.org/I4405286254"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaobo Zhou","raw_affiliation_strings":["Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Radiology, The Methodist Hospital Research Institute & Weill Cornell Medical College of Cornell University, Houston, USA","institution_ids":["https://openalex.org/I205783295","https://openalex.org/I4405286254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089711319","display_name":"Guozheng Li","orcid":"https://orcid.org/0000-0001-5568-0347","observed_orcids":["https://orcid.org/0000-0001-5568-0347"]},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guo-Zheng Li","raw_affiliation_strings":["Department of Control Science & Engineering, Tongji University, Shanghai, China","Dept.of Control Science and Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Control Science & Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"Dept.of Control Science and Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":10.7237,"has_fulltext":true,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97769042,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"12","issue":"1","first_page":"127","last_page":"127"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.7865999937057495,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.7865999937057495,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative 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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.07559999823570251,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.05079999938607216,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/traditional-chinese-medicine","display_name":"traditional Chinese medicine","score":0.6740000247955322},{"id":"https://openalex.org/keywords/computer-aided-diagnosis","display_name":"computer-aided diagnosis","score":0.8479999899864197},{"id":"https://openalex.org/keywords/multiclass-support-vector-machine","display_name":"multi-class support vector machine","score":0.8410000205039978},{"id":"https://openalex.org/keywords/weighted-support-vector-machine","display_name":"weighted support vector machine","score":0.8059999942779541},{"id":"https://openalex.org/keywords/svm-rfe","display_name":"SVM-RFE","score":0.7160000205039978},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.8579999804496765},{"id":"https://openalex.org/keywords/color-features","display_name":"color features","score":0.49399998784065247},{"id":"https://openalex.org/keywords/texture-features","display_name":"texture features","score":0.9950000047683716},{"id":"https://openalex.org/keywords/moment-features","display_name":"moment features","score":0.9700000286102295},{"id":"https://openalex.org/keywords/syndrome-diagnosis","display_name":"syndrome diagnosis","score":0.6129999756813049},{"id":"https://openalex.org/keywords/k-nearest-neighbors","display_name":"k-nearest neighbors","score":0.6179999709129333},{"id":"https://openalex.org/keywords/naive-bayes","display_name":"naive Bayes","score":0.7580000162124634},{"id":"https://openalex.org/keywords/information-gain","display_name":"information gain","score":0.5120000243186951},{"id":"https://openalex.org/keywords/minimum-redundancy-maximum-relevance","display_name":"minimum redundancy maximum relevance","score":0.8050000071525574},{"id":"https://openalex.org/keywords/classification-accuracy-comparison","display_name":"classification accuracy comparison","score":0.5339999794960022},{"id":"https://openalex.org/keywords/medical-image-classification","display_name":"medical image classification","score":0.31700000166893005}],"concepts":[{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.7657497525215149},{"id":"https://openalex.org/C556039675","wikidata":"https://www.wikidata.org/wiki/Q771035","display_name":"Traditional medicine","level":1,"score":0.6238330602645874},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5692751407623291},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.521701991558075},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"score":0.4852580726146698},{"id":"https://openalex.org/C188947578","wikidata":"https://www.wikidata.org/wiki/Q200253","display_name":"Traditional Chinese medicine","level":3,"score":0.47173941135406494},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35559022426605225},{"id":"https://openalex.org/C512399662","wikidata":"https://www.wikidata.org/wiki/Q3505712","display_name":"Family medicine","level":1,"score":0.3228609561920166},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.16128253936767578},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.13688042759895325}],"mesh":[{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000328","descriptor_name":"Adult","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D000368","descriptor_name":"Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D001499","descriptor_name":"Bayes Theorem","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003116","descriptor_name":"Color","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003116","descriptor_name":"Color","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003116","descriptor_name":"Color","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003936","descriptor_name":"Diagnosis, Computer-Assisted","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D003937","descriptor_name":"Diagnosis, Differential","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003937","descriptor_name":"Diagnosis, Differential","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003937","descriptor_name":"Diagnosis, Differential","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D005260","descriptor_name":"Female","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":"D008046","descriptor_name":"Lip","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008046","descriptor_name":"Lip","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008046","descriptor_name":"Lip","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008297","descriptor_name":"Male","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008516","descriptor_name":"Medicine, Chinese Traditional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008516","descriptor_name":"Medicine, Chinese Traditional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008516","descriptor_name":"Medicine, Chinese Traditional","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008875","descriptor_name":"Middle Aged","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D010363","descriptor_name":"Pattern Recognition, Automated","qualifier_ui":"Q000379","qualifier_name":"methods","is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016018","descriptor_name":"Least-Squares Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D060388","descriptor_name":"Support Vector Machine","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":4,"locations":[{"id":"doi:10.1186/1472-6882-12-127","doi":"https://doi.org/10.1186/1472-6882-12-127","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1472-6882-12-127","pdf_url":"https://bmccomplementmedtherapies.biomedcentral.com/counter/pdf/10.1186/1472-6882-12-127","source":{"id":"https://openalex.org/S163220592","display_name":"BMC Complementary and Alternative Medicine","issn_l":"1472-6882","issn":["1472-6882"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","ki-jl-1","poland-100","vabb-shw"],"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Complementary and Alternative Medicine","raw_type":"journal-article"},{"id":"pmid:22898352","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/22898352","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":"BMC complementary and alternative medicine","raw_type":"Journal Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:3522569","doi":null,"is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/3522569","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"BMC Complement Altern Med","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:55ef60d5a0124d9fb8e6607cf4bfd85e","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/55ef60d5a0124d9fb8e6607cf4bfd85e","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":"BMC Complementary and Alternative Medicine, Vol 12, Iss 1, p 127 (2012)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/1472-6882-12-127","doi":"https://doi.org/10.1186/1472-6882-12-127","is_oa":true,"landing_page_url":"https://doi.org/10.1186/1472-6882-12-127","pdf_url":"https://bmccomplementmedtherapies.biomedcentral.com/counter/pdf/10.1186/1472-6882-12-127","source":{"id":"https://openalex.org/S163220592","display_name":"BMC Complementary and Alternative Medicine","issn_l":"1472-6882","issn":["1472-6882"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","ki-jl-1","poland-100","vabb-shw"],"host_organization":"https://openalex.org/P4310320256","host_organization_name":"BioMed Central","host_organization_lineage":["https://openalex.org/P4310320256","https://openalex.org/P4310319965"],"host_organization_lineage_names":["BioMed Central","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"BMC Complementary and Alternative Medicine","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.9391000270843506}],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.4699999988079071}],"study_designs":[],"awards":[{"id":"https://openalex.org/G2202736887","display_name":null,"funder_award_id":"S30302","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5741089003","display_name":"\u57fa\u4e8e\u591a\u79cd\u4fe1\u606f\u5904\u7406\u6280\u672f\u7684\u9762\u8272\u8bca\u4fe1\u606f\u81ea\u52a8\u8bc6\u522b\u7814\u7a76","funder_award_id":"30600796","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2129456158.pdf","grobid_xml":"https://content.openalex.org/works/W2129456158.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W627818147","https://openalex.org/W1802038978","https://openalex.org/W2034415234","https://openalex.org/W2044465660","https://openalex.org/W2049332898","https://openalex.org/W2057315055","https://openalex.org/W2059432853","https://openalex.org/W2072916379","https://openalex.org/W2073105997","https://openalex.org/W2075056274","https://openalex.org/W2095717214","https://openalex.org/W2097599147","https://openalex.org/W2099619800","https://openalex.org/W2107294643","https://openalex.org/W2107956883","https://openalex.org/W2109098835","https://openalex.org/W2116060898","https://openalex.org/W2118585731","https://openalex.org/W2119466907","https://openalex.org/W2123895705","https://openalex.org/W2129248810","https://openalex.org/W2141955292","https://openalex.org/W2143426320","https://openalex.org/W2149099097","https://openalex.org/W2153444770","https://openalex.org/W2153635508","https://openalex.org/W2154053567","https://openalex.org/W2161082673","https://openalex.org/W2399208270","https://openalex.org/W2435251607","https://openalex.org/W3152227378"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2392684411","https://openalex.org/W2397639394","https://openalex.org/W4323904150","https://openalex.org/W2368337640","https://openalex.org/W2370858806","https://openalex.org/W2372843101","https://openalex.org/W2381806105","https://openalex.org/W2471297334"],"abstract_inverted_index":{"BACKGROUND:":[0],"In":[1,101,236],"Traditional":[2],"Chinese":[3],"Medicine":[4],"(TCM),":[5],"the":[6,36,42,45,69,75,87,92,118,124,141,149,168,184,223,257,269,281,323,328,333,341,355,382,389,396,401,405,430,433,439,464,473,482,500,532],"lip":[7,24,93,125,142,150,169,185,225,276,284,376,431,465,514,536],"diagnosis":[8,76,94,119,138,258,285,505,537,548],"is":[9,20,29,49,59,132,146,196,219,344,364,425,469,478,509],"an":[10,112],"important":[11,295],"diagnostic":[12,47,423],"method":[13,131,291,528],"which":[14,58,297,427],"has":[15],"a":[16,27,32,106,526,544],"long":[17],"history":[18],"and":[19,61,72,77,99,114,134,158,177,190,213,231,253,308,348,368,375,387,416,444,459,493,503,520,529],"applied":[21,135,479],"widely.":[22],"The":[23,63,160,179,288,336,359],"color":[25,186,302],"of":[26,39,95,120,164,274,283,300,340,362,393,451,507,538],"person":[28],"considered":[30],"as":[31,540,542],"symptom":[33],"to":[34,85,110,147,471,480,495,511],"reflect":[35],"physical":[37],"conditions":[38],"organs":[40],"in":[41,79,286,549],"body.":[43],"However,":[44],"traditional":[46],"approach":[48,65,116],"mainly":[50],"based":[51,90,122,139,221,321,437],"on":[52,68,91,123,140,222,322,370,438,463,535],"observation":[53],"by":[54,198],"doctor's":[55,70],"nude":[56],"eyes,":[57],"non-quantitative":[60,64],"subjective.":[62],"largely":[66],"depends":[67],"experience":[71],"influences":[73],"accurate":[74],"treatment":[78],"TCM.":[80,287,550],"Developing":[81],"new":[82,527],"quantification":[83],"methods":[84,343],"identify":[86],"exact":[88],"syndrome":[89,137],"TCM":[96,121,508],"becomes":[97],"urgent":[98],"important.":[100],"this":[102],"paper,":[103],"we":[104,238,486],"design":[105],"computer-assisted":[107,129],"classification":[108,130,319,338,357,360,391,398,410],"model":[109,218,443],"provide":[111],"automatic":[113,502],"quantitative":[115,504,533],"for":[117,136,256,280,531,546],"images.":[126,143],"METHODS:":[127],"A":[128,272,422],"designed":[133],"Our":[144],"purpose":[145],"classify":[148,481],"images":[151,277],"into":[152],"four":[153,165,483,513],"groups:":[154],"deep-red,":[155],"red,":[156],"purple":[157],"pale.":[159],"proposed":[161],"scheme":[162],"consists":[163],"steps":[166],"including":[167],"image":[170,172,226,264,377,436,515],"preprocessing,":[171],"feature":[173,175,206,289,383,418,490],"extraction,":[174],"selection":[176,195,290,384,419,491],"classification.":[178],"extracted":[180],"84":[181,334],"features":[182,227,296,307,326,452,458],"contain":[183],"space":[187,454],"component,":[188],"texture":[189,306],"moment":[191,310,461],"features.":[192,335,475],"Feature":[193],"subset":[194],"performed":[197],"using":[199,228],"SVM-RFE":[200,292],"(Support":[201],"Vector":[202],"Machine":[203],"with":[204,241,381,413],"recursive":[205],"elimination),":[207],"mRMR":[208,386],"(minimum":[209],"Redundancy":[210],"Maximum":[211],"Relevance)":[212],"IG":[214],"(information":[215],"gain).":[216],"Classification":[217],"constructed":[220],"collected":[224,279],"multi-class":[229,233],"SVM":[230,234,240,353,363,414,477],"Weighted":[232],"(WSVM).":[235],"addition,":[237],"compare":[239,488],"k-nearest":[242],"neighbor":[243],"(kNN)":[244],"algorithm,":[245],"Multiple":[246],"Asymmetric":[247],"Partial":[248],"Least":[249],"Squares":[250],"Classifier":[251],"(MAPLSC)":[252],"Na\u00efve":[254,314],"Bayes":[255],"performance":[259],"comparison.":[260],"All":[261],"displayed":[262],"faces":[263],"have":[265],"obtained":[266,330],"consent":[267],"from":[268,331,432],"participants.":[270],"RESULTS:":[271],"total":[273,337,390],"257":[275],"are":[278,298],"modeling":[282],"selects":[293],"9":[294,324],"composed":[299],"5":[301],"component":[303],"features,":[304,455],"3":[305],"1":[309],"feature.":[311],"SVM,":[312],"MAPLSC,":[313],"Bayes,":[315],"kNN":[316],"showed":[317],"better":[318],"results":[320,329,402],"selected":[325],"than":[327],"all":[332],"accuracy":[339,361,392,411],"five":[342],"84%,":[345],"81%,":[346,349,365],"79%":[347],"77%,":[350],"respectively.":[351,379],"So":[352,499],"achieves":[354,395],"best":[356,397,409],"accuracy.":[358,399],"71%,":[366],"89%":[367],"86%":[369],"Deep-red,":[371,517],"Pale":[372],"Purple,":[373,518],"Red":[374,519],"models,":[378],"While":[380],"algorithm":[385],"IG,":[388],"WSVM":[394],"Therefore,":[400],"show":[403],"that":[404],"system":[406,424,506],"can":[407],"achieve":[408],"combined":[412],"classifiers":[415,494],"SVM-REF":[417,468],"algorithm.":[420],"CONCLUSIONS:":[421],"proposed,":[426],"firstly":[428],"segments":[429],"original":[434],"facial":[435],"Chan-Vese":[440],"level":[441],"set":[442],"Otsu":[445],"method,":[446],"then":[447],"extracts":[448],"three":[449],"kinds":[450],"(color":[453],"Haralick":[456],"co-occurrence":[457],"Zernike":[460],"features)":[462],"image.":[466],"Meanwhile,":[467],"adopted":[470],"select":[472],"optimal":[474],"Finally,":[476],"classes.":[484],"Besides,":[485],"also":[487],"different":[489],"algorithms":[492],"verify":[496],"our":[497],"system.":[498],"developed":[501],"effective":[510],"distinguish":[512],"classes:":[516],"Pale.":[521],"This":[522],"study":[523],"puts":[524],"forward":[525],"idea":[530],"examination":[534],"TCM,":[539],"well":[541],"provides":[543],"template":[545],"objective":[547]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":3}],"updated_date":"2026-10-24T09:50:30.924529","created_date":"2025-10-10T00:00:00"}
