{"id":"https://openalex.org/W2979724898","doi":"https://doi.org/10.1145/3357419.3357436","title":"A Recommendation Model for Medical Data Visualization Based on Information Entropy and Decision Tree Optimized by Two Correlation Coefficients","display_name":"A Recommendation Model for Medical Data Visualization Based on Information Entropy and Decision Tree Optimized by Two Correlation Coefficients","publication_year":2019,"publication_date":"2019-08-23","ids":{"openalex":"https://openalex.org/W2979724898","doi":"https://doi.org/10.1145/3357419.3357436","mag":"2979724898"},"language":"en","primary_location":{"id":"doi:10.1145/3357419.3357436","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357419.3357436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Information Communication and Management","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/A5046448499","display_name":"Huishan Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huishan Huang","raw_affiliation_strings":["School of Economics and Management, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008891083","display_name":"Runtong Zhang","orcid":"https://orcid.org/0000-0003-0246-5058"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Runtong Zhang","raw_affiliation_strings":["School of Economics and Management, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033291319","display_name":"Xinyi Lu","orcid":"https://orcid.org/0000-0001-9379-4935"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Lu","raw_affiliation_strings":["School of Economics and Management, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5046448499"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.42,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.71517523,"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":"52","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10862","display_name":"AI in cancer detection","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10862","display_name":"AI in cancer detection","score":0.9818999767303467,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9764999747276306,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9635999798774719,"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/computer-science","display_name":"Computer science","score":0.7122149467468262},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6922953128814697},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6589401960372925},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6579233407974243},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6267816424369812},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.5895407199859619},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5619295239448547},{"id":"https://openalex.org/keywords/pearson-product-moment-correlation-coefficient","display_name":"Pearson product-moment correlation coefficient","score":0.4442176818847656},{"id":"https://openalex.org/keywords/decision-tree-learning","display_name":"Decision tree learning","score":0.4386734068393707},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.42154228687286377},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3246954679489136},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31557756662368774},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18949899077415466},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18854084610939026}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7122149467468262},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6922953128814697},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6589401960372925},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6579233407974243},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6267816424369812},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.5895407199859619},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5619295239448547},{"id":"https://openalex.org/C55078378","wikidata":"https://www.wikidata.org/wiki/Q1136628","display_name":"Pearson product-moment correlation coefficient","level":2,"score":0.4442176818847656},{"id":"https://openalex.org/C5481197","wikidata":"https://www.wikidata.org/wiki/Q16766476","display_name":"Decision tree learning","level":3,"score":0.4386734068393707},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.42154228687286377},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3246954679489136},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31557756662368774},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18949899077415466},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18854084610939026},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3357419.3357436","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357419.3357436","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 9th International Conference on Information Communication and Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.4399999976158142,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W56793145","https://openalex.org/W1584845053","https://openalex.org/W1785697160","https://openalex.org/W1982821459","https://openalex.org/W1994338652","https://openalex.org/W1995491659","https://openalex.org/W2000845576","https://openalex.org/W2055788552","https://openalex.org/W2087487085","https://openalex.org/W2089367555","https://openalex.org/W2091300755","https://openalex.org/W2096059947","https://openalex.org/W2141083048","https://openalex.org/W2141441962","https://openalex.org/W2141910941","https://openalex.org/W2147700937","https://openalex.org/W2152510616","https://openalex.org/W2189223557","https://openalex.org/W2273048275","https://openalex.org/W2321990803","https://openalex.org/W2398606097","https://openalex.org/W2492547921","https://openalex.org/W2550936871","https://openalex.org/W2589355034","https://openalex.org/W2778314063","https://openalex.org/W2783033253","https://openalex.org/W4252180116"],"related_works":["https://openalex.org/W357196361","https://openalex.org/W3109425891","https://openalex.org/W2027314909","https://openalex.org/W1036938216","https://openalex.org/W2113714434","https://openalex.org/W2377792686","https://openalex.org/W4200439127","https://openalex.org/W829658220","https://openalex.org/W3096637473","https://openalex.org/W2946560178"],"abstract_inverted_index":{"Medical":[0],"practitioners":[1],"usually":[2],"have":[3],"difficulties":[4],"in":[5,85,101,140],"obtaining":[6],"information":[7,34,98],"effectively":[8],"from":[9],"massive":[10],"data":[11,27],"due":[12],"to":[13,77,103],"limited":[14],"time":[15],"and":[16,33,46,83,143],"energy.":[17],"This":[18],"paper":[19],"proposes":[20],"a":[21,60,117],"novel":[22],"recommendation":[23],"model":[24],"for":[25],"medical":[26,56,61,93,125],"visualization":[28,52],"based":[29,95],"on":[30,96],"decision":[31,64,106],"tree":[32,65,107],"entropy":[35],"optimized":[36],"by":[37],"two":[38,68],"correlation":[39,44,48,69],"coefficients,":[40],"that":[41,112,137],"is,":[42],"Pearson's":[43],"coefficient":[45],"Kendall's":[47],"coefficient(P&K.CC).":[49],"After":[50],"investigating":[51],"techniques":[53],"under":[54],"different":[55],"scenarios,":[57],"we":[58],"construct":[59],"domain":[62],"knowledge-based":[63],"which":[66],"employs":[67],"coefficients":[70],"as":[71,88,90],"new":[72],"measures":[73],"of":[74,120,124],"feature":[75],"quality":[76],"confirm":[78],"the":[79,92,109,113,121,128,131,135],"optimal":[80],"splitting":[81],"attributes":[82],"points":[84],"its":[86],"growth,":[87],"well":[89],"prioritize":[91],"datasets":[94,136],"improved":[97],"entropy.":[99],"Finally,":[100],"contrast":[102],"several":[104],"traditional":[105],"classifiers,":[108],"results":[110],"indicated":[111],"proposed":[114],"method":[115,132],"achieves":[116],"better":[118,139],"accuracy":[119],"scenario":[122],"classification":[123],"data.":[126],"At":[127],"same":[129],"time,":[130],"can":[133],"find":[134],"perform":[138],"knowledge":[141],"presentation":[142],"visualization.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
