{"id":"https://openalex.org/W3127893270","doi":"https://doi.org/10.1109/bibm49941.2020.9313140","title":"A Support Vector Machine Learning for the Upward and Downward Tendency Theory of Traditional Chinese Medicine","display_name":"A Support Vector Machine Learning for the Upward and Downward Tendency Theory of Traditional Chinese Medicine","publication_year":2020,"publication_date":"2020-12-16","ids":{"openalex":"https://openalex.org/W3127893270","doi":"https://doi.org/10.1109/bibm49941.2020.9313140","mag":"3127893270"},"language":"en","primary_location":{"id":"doi:10.1109/bibm49941.2020.9313140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","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/A5100696378","display_name":"Hongyan Cheng","orcid":"https://orcid.org/0000-0001-5662-9981"},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyan Cheng","raw_affiliation_strings":["Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, GD, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, GD, China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101619209","display_name":"Zhiwei Liang","orcid":"https://orcid.org/0000-0002-4243-0354"},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Liang","raw_affiliation_strings":["Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Dongguan, GD, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Dongguan, GD, China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019013550","display_name":"Zhongquan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongquan Huang","raw_affiliation_strings":["Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, GD, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, GD, China","institution_ids":["https://openalex.org/I117532281"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102186053","display_name":"Xipeng Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I117532281","display_name":"Guangzhou University of Chinese Medicine","ror":"https://ror.org/03qb7bg95","country_code":"CN","type":"education","lineage":["https://openalex.org/I117532281"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xipeng YU","raw_affiliation_strings":["Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Dongguan, GD, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dongguan & Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Guangzhou University of Chinese Medicine, Dongguan, GD, China","institution_ids":["https://openalex.org/I117532281"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I117532281"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26215699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1526","last_page":"1533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9986000061035156,"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":0.9986000061035156,"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/T11709","display_name":"Traditional Chinese Medicine Analysis","score":0.9901999831199646,"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/T10836","display_name":"Metabolomics and Mass Spectrometry Studies","score":0.9836000204086304,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6911485195159912},{"id":"https://openalex.org/keywords/traditional-chinese-medicine","display_name":"Traditional Chinese medicine","score":0.6235436201095581},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5947935581207275},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.47552135586738586},{"id":"https://openalex.org/keywords/traditional-medicine","display_name":"Traditional medicine","score":0.46074286103248596},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.45532870292663574},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.402723103761673},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37471428513526917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3484797179698944},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.21386244893074036},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.09184321761131287}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6911485195159912},{"id":"https://openalex.org/C188947578","wikidata":"https://www.wikidata.org/wiki/Q200253","display_name":"Traditional Chinese medicine","level":3,"score":0.6235436201095581},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5947935581207275},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.47552135586738586},{"id":"https://openalex.org/C556039675","wikidata":"https://www.wikidata.org/wiki/Q771035","display_name":"Traditional medicine","level":1,"score":0.46074286103248596},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.45532870292663574},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.402723103761673},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37471428513526917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3484797179698944},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.21386244893074036},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.09184321761131287},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bibm49941.2020.9313140","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bibm49941.2020.9313140","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2017994420","https://openalex.org/W2117479478","https://openalex.org/W2121893605","https://openalex.org/W2126832653","https://openalex.org/W2362499484","https://openalex.org/W2609893130","https://openalex.org/W2739434068","https://openalex.org/W2811422905","https://openalex.org/W2922475140","https://openalex.org/W3012139728","https://openalex.org/W3046205893"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2051187167","https://openalex.org/W1980100242"],"abstract_inverted_index":{"Objective:":[0],"In":[1],"order":[2],"to":[3,206,335,356,394,458],"study":[4],"the":[5,18,34,37,53,65,85,92,95,99,117,122,173,201,218,240,263,269,279,288,292,298,305,313,320,340,346,351,368,377,387,402,408,425,448,460,464],"traditional":[6],"Chinese":[7],"medicine":[8],"(TCM)":[9],"drug":[10,39,61,77,124,155,265,277,439],"property":[11],"theory":[12],"based":[13],"on":[14,36,345],"machine":[15,21],"learning":[16,227,299],"(ML),":[17],"support":[19],"vector":[20,150,167,375],"(SVM)":[22],"as":[23,84,164,181,371],"a":[24,59,71,112,165,226,244,250,309,327],"powerful":[25],"model":[26,260,290],"in":[27,44,116,138,168,186,339],"ML":[28],"is":[29],"worthy":[30],"of":[31,74,103,141,198,236,278,332,376,386,405,412,437,447],"exploring":[32],"for":[33,64,214,225,249,261,416,463],"distinguish":[35],"TCM":[38,60,67,76,100,123,128,154,158,203,237,264,276,378,432,438,443,465],"Upward":[40,420],"and":[41,51,56,98,110,133,148,217,291,324,350,366,392,422,452],"Downward":[42,388,417,467],"Tendency":[43,160,389,421],"this":[45],"theory.":[46],"Methods:":[47],"1.":[48],"To":[49,120,144,256],"select":[50],"include":[52],"research":[54],"materials":[55],"objects.":[57],"From":[58],"textbook":[62],"applying":[63],"state":[66],"university":[68],"education":[69],"(TBTCMUE),":[70],"total":[72,321],"(t)":[73],"135":[75,202],"was":[78,285,316,390,407],"selected,":[79],"containing":[80],"necessary":[81],"features":[82,102,130,175,426,445],"such":[83],"main":[86],"chemical":[87],"structure":[88],"among":[89],"active":[90],"ingredients,":[91],"botany":[93],"Family,":[94],"Medicinal":[96,369],"Part,":[97],"drug's":[101,129,159,379,433,444,466],"Four-Qi":[104],"or":[105,108,176,228,252,442],"Cold-Heat,":[106],"Five-Taste":[107],"Flavor,":[109],"Tendency,":[111,424],"known":[113],"classification":[114],"feature":[115,161,374,434],"TBTCMUE.":[118],"2.":[119],"establish":[121],"features'":[125],"coding":[126],"rules.":[127],"were":[131,362],"digitized":[132],"coded":[134],"with":[135,348],"domain":[136],"code-values":[137],"different":[139,358],"levels":[140],"extent.":[142],"3.":[143],"build":[145],"template,":[146],"training,":[147],"pattern":[149,251,280,341,359],"data":[151],"sets":[152],"from":[153,200,296,312],"features.":[156],"Each":[157],"can":[162,454],"suppose":[163,180],"column":[166,184],"matrix":[169,188,210,221,245],"T(:,":[170],"1),":[171,274],"whereas":[172],"other":[174],"their":[177],"combinations":[178],"could":[179,242],"corresponding":[182],"numbers":[183,194,235],"vectors":[185,415,435],"another":[187],"L(:,":[189],"c).":[190,303],"Meanwhile,":[191],"extract":[192],"r":[193,208],"(r":[195],"<;":[196],"t)":[197],"drugs":[199,204,238],"(t=135)":[205],"create":[207,257],"rows":[209,220],"T":[211,272],"(r,":[212,223,273,302],"1)":[213],"template":[215,270],"set":[216,271,281,300],"same":[219],"L":[222,301],"c)":[224,248],"training":[229],"set.":[230,254],"The":[231,431],"left":[232],"p":[233],"(p=t-r)":[234],"after":[239],"extraction":[241],"form":[243],"P":[246,282],"(p,":[247,283],"testing":[253],"4.":[255],"an":[258,336,396],"SVM":[259,289,294,349,352],"recognizing":[262],"Tendency.":[266,418,468],"By":[267],"matching":[268,322],"each":[275,357],"c),":[284],"recognized":[286],"by":[287,319,364],"trained":[293],"rule":[295,354],"its":[297,383],"Then,":[304],"matched":[306,314,384,403],"rate":[307,385,404],"expected,":[308],"value":[310,330],"counted":[311,317],"results,":[315],"divided":[318],"count":[323],"greater":[325],"than":[326],"supposing":[328],"threshold":[329],"(THV)":[331],"0.75,":[333],"referring":[334],"acceptable":[337,397],"result":[338],"recognition.":[342],"Results:":[343],"Based":[344],"recognition":[347],"algorithm":[353],"relative":[355],"when":[360],"parameters":[361],"specified":[363],"p=1":[365],"r=tp=134,":[367],"Parts,":[370,441],"one":[372],"single":[373],"features,":[380],"showed":[381],"that":[382],"0.8":[391],"referred":[393],"be":[395,455],"outcome.":[398],"Another":[399],"accepted":[400],"at":[401],"0.75":[406],"Family-Flavor-Benzene-atom":[409],"combination":[410,414,446],"group":[411],"four-feature":[413],"For":[419],"Dual":[423],"had":[427],"unacceptable":[428],"results.":[429],"Conclusion:":[430],"composed":[436],"Medical":[440],"family,":[449],"flavor,":[450],"Benzene,":[451],"atom,":[453],"helpfully":[456],"utilized":[457],"reveal":[459],"contributing":[461],"factors":[462]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
